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LaCour!: Enabling Research on Argumentation in Hearings of the European Court of Human Rights (2312.05061v4)
Published 8 Dec 2023 in cs.CL
Abstract: Why does an argument end up in the final court decision? Was it deliberated or questioned during the oral hearings? Was there something in the hearings that triggered a particular judge to write a dissenting opinion? Despite the availability of the final judgments of the European Court of Human Rights (ECHR), none of these legal research questions can currently be answered as the ECHR's multilingual oral hearings are not transcribed, structured, or speaker-attributed. We address this fundamental gap by presenting LaCour!, the first corpus of textual oral arguments of the ECHR, consisting of 154 full hearings (2.1 million tokens from over 267 hours of video footage) in English, French, and other court languages, each linked to the corresponding final judgment documents. In addition to the transcribed and partially manually corrected text from the video, we provide sentence-level timestamps and manually annotated role and language labels. We also showcase LaCour! in a set of preliminary experiments that explore the interplay between questions and dissenting opinions. Apart from the use cases in legal NLP, we hope that law students or other interested parties will also use LaCour! as a learning resource, as it is freely available in various formats at https://huggingface.co/datasets/TrustHLT/LaCour.
- Ashley K, Pinkwart N, Lynch C, et al (2007) Learning by Diagramming Supreme Court Oral Arguments. In: Proceedings of the 11th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’07, pp 271–275, 10.1145/1276318.1276370 Bergam et al (2022) Bergam N, Allaway E, McKeown K (2022) Legal and Political Stance Detection of SCOTUS Language. In: Proceedings of the Natural Legal Language Processing Workshop 2022. Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), pp 265–275, 10.18653/v1/2022.nllp-1.25 Bredin et al (2020) Bredin H, Yin R, Coria JM, et al (2020) Pyannote.Audio: Neural Building Blocks for Speaker Diarization. In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 7124–7128, 10.1109/ICASSP40776.2020.9052974 Chalkidis et al (2019) Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Bergam N, Allaway E, McKeown K (2022) Legal and Political Stance Detection of SCOTUS Language. In: Proceedings of the Natural Legal Language Processing Workshop 2022. Association for Computational Linguistics, Abu Dhabi, United Arab Emirates (Hybrid), pp 265–275, 10.18653/v1/2022.nllp-1.25 Bredin et al (2020) Bredin H, Yin R, Coria JM, et al (2020) Pyannote.Audio: Neural Building Blocks for Speaker Diarization. In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 7124–7128, 10.1109/ICASSP40776.2020.9052974 Chalkidis et al (2019) Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Bredin H, Yin R, Coria JM, et al (2020) Pyannote.Audio: Neural Building Blocks for Speaker Diarization. In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 7124–7128, 10.1109/ICASSP40776.2020.9052974 Chalkidis et al (2019) Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Bredin H, Yin R, Coria JM, et al (2020) Pyannote.Audio: Neural Building Blocks for Speaker Diarization. In: ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 7124–7128, 10.1109/ICASSP40776.2020.9052974 Chalkidis et al (2019) Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. 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Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. 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URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Androutsopoulos I, Aletras N (2019) Neural Legal Judgment Prediction in English. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Association for Computational Linguistics, Florence, Italy, pp 4317–4323, 10.18653/v1/P19-1424 Chalkidis et al (2020) Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Fergadiotis M, Malakasiotis P, et al (2020) LEGAL-BERT: The Muppets Straight out of Law School. In: Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, pp 2898–2904, 10.18653/v1/2020.findings-emnlp.261 Chalkidis et al (2022) Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. 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Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. 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Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Chalkidis I, Jana A, Hartung D, et al (2022) LexGLUE: A Benchmark Dataset for Legal Language Understanding in English. In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Dublin, Ireland, pp 4310–4330, 10.18653/v1/2022.acl-long.297 Dickinson (2018) Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. 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URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. 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- Dickinson GM (2018) A Computational Analysis Of Oral Argument In The Supreme Court. Cornell Journal of Law and Policy 28(3):449 Goldman (1998) Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Goldman J (1998) Political Science: Multimedia for Research and Teaching—The Oyez Oyez Oyez and the History and Politics Out Loud Projects. Social Science Computer Review 16(1):30–39. 10.1177/089443939801600105 Habernal et al (2023) Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Habernal I, Faber D, Recchia N, et al (2023) Mining Legal Arguments in Court Decisions. Artificial Intelligence and Law 10.1007/s10506-023-09361-y Henderson et al (2022) Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. 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Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Henderson P, Krass M, Zheng L, et al (2022) Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset. Advances in Neural Information Processing Systems 35:29,217–29,234 Johnson et al (2009) Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. 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URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. 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URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. 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IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. 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In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. 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Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6
- Johnson TR, Black RC, Goldman J, et al (2009) Inquiring Minds Want to Know: Do Justices Tip Their Hands with Questions at Oral Argument in the U.S. Supreme Court. Washington University Journal of Law & Policy 29:241 Medvedeva et al (2020) Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Medvedeva M, Vols M, Wieling M (2020) Using Machine Learning to Predict Decisions of the European Court of Human Rights. Artificial Intelligence and Law 28(2):237–266. 10.1007/s10506-019-09255-y Mochales and Ieven (2009) Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Ieven A (2009) Creating an Argumentation Corpus: Do Theories Apply to Real Arguments? A Case Study on the Legal Argumentation of the ECHR. In: Proceedings of the 12th International Conference on Artificial Intelligence and Law. Association for Computing Machinery, New York, NY, USA, ICAIL ’09, pp 21–30, 10.1145/1568234.1568238 Mochales and Moens (2011) Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics, Hong Kong, China, pp 3982–3992, 10.18653/v1/D19-1410, URL https://aclanthology.org/D19-1410 Spaeth et al (2022) Spaeth HJ, Epstein L, Martin AD, et al (2022) 2022 Supreme Court Database, Version 2022 Release 01. URL http://Supremecourtdatabase.org Villata et al (2022) Villata S, Araszkiewicz M, Ashley K, et al (2022) Thirty Years of Artificial Intelligence and Law: The Third Decade. Artificial Intelligence and Law 30(4):561–591. 10.1007/s10506-022-09327-6 Mochales R, Moens MF (2011) Argumentation Mining. Artificial Intelligence and Law 19(1):1–22. 10.1007/s10506-010-9104-x Mochales-Palau and Moens (2007) Mochales-Palau R, Moens MF (2007) Study on Sentence Relations in the Automatic Detection of Argumentation in Legal Cases. In: Proceedings of the 2007 Conference on Legal Knowledge and Information Systems: JURIX 2007: The Twentieth Annual Conference. IOS Press, NLD, pp 89–98 Poudyal et al (2020) Poudyal P, Savelka J, Ieven A, et al (2020) ECHR: Legal Corpus for Argument Mining. In: Proceedings of the 7th Workshop on Argument Mining. Association for Computational Linguistics, Online, pp 67–75 Radford et al (2023) Radford A, Kim JW, Xu T, et al (2023) Robust Speech Recognition via Large-Scale Weak Supervision. In: Krause A, Brunskill E, Cho K, et al (eds) Proceedings of the 40th International Conference on Machine Learning, Proceedings of Machine Learning Research, vol 202. PMLR, pp 28,492–28,518, URL https://proceedings.mlr.press/v202/radford23a.html Reimers and Gurevych (2019) Reimers N, Gurevych I (2019) Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In: Inui K, Jiang J, Ng V, et al (eds) Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 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