2000 character limit reached
ProMoAI: Process Modeling with Generative AI (2403.04327v2)
Published 7 Mar 2024 in cs.DB and cs.CL
Abstract: ProMoAI is a novel tool that leverages LLMs to automatically generate process models from textual descriptions, incorporating advanced prompt engineering, error handling, and code generation techniques. Beyond automating the generation of complex process models, ProMoAI also supports process model optimization. Users can interact with the tool by providing feedback on the generated model, which is then used for refining the process model. ProMoAI utilizes the capabilities LLMs to offer a novel, AI-driven approach to process modeling, significantly reducing the barrier to entry for users without deep technical knowledge in process modeling.
- Gemini: A family of highly capable multimodal models. CoRR, abs/2312.11805, 2023.
- A qualitative analysis of the state of the art in process extraction from text. In Giuseppe Vizzari, Matteo Palmonari, and Andrea Orlandini, editors, Proceedings of the AIxIA 2020 Discussion Papers Workshop co-located with the the 19th International Conference of the Italian Association for Artificial Intelligence (AIxIA2020), Anywhere, November 27th, 2020, volume 2776 of CEUR Workshop Proceedings, pages 19–30. CEUR-WS.org, 2020.
- PET: an annotated dataset for process extraction from natural language text tasks. In Cristina Cabanillas, Niels Frederik Garmann-Johnsen, and Agnes Koschmider, editors, Business Process Management Workshops - BPM 2022 International Workshops, Münster, Germany, September 11-16, 2022, Revised Selected Papers, volume 460 of Lecture Notes in Business Information Processing, pages 315–321. Springer, 2022.
- Abstractions, scenarios, and prompt definitions for process mining with llms: A case study. In Jochen De Weerdt and Luise Pufahl, editors, Business Process Management Workshops - BPM 2023 International Workshops, Utrecht, The Netherlands, September 11-15, 2023, Revised Selected Papers, volume 492 of Lecture Notes in Business Information Processing, pages 427–439. Springer, 2023.
- Language models are few-shot learners. In Hugo Larochelle, Marc’Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, and Hsuan-Tien Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020.
- Just tell me: Prompt engineering in business process management. In Han van der Aa, Dominik Bork, Henderik A. Proper, and Rainer Schmidt, editors, Enterprise, Business-Process and Information Systems Modeling - 24th International Conference, BPMDS 2023, and 28th International Conference, EMMSAD 2023, Zaragoza, Spain, June 12-13, 2023, Proceedings, volume 479 of Lecture Notes in Business Information Processing, pages 3–11. Springer, 2023.
- Let me tell you a story - on how to build process models. J. Univers. Comput. Sci., 17(2):276–295, 2011.
- Generative AI. Bus. Inf. Syst. Eng., 66(1):111–126, 2024.
- Conceptual modeling and large language models: Impressions from first experiments with chatgpt. Enterp. Model. Inf. Syst. Archit. Int. J. Concept. Model., 18:3, 2023.
- Process model generation from natural language text. In Haralambos Mouratidis and Colette Rolland, editors, Advanced Information Systems Engineering - 23rd International Conference, CAiSE 2011, London, UK, June 20-24, 2011. Proceedings, volume 6741 of Lecture Notes in Computer Science, pages 482–496. Springer, 2011.
- Large language models can accomplish business process management tasks. In Jochen De Weerdt and Luise Pufahl, editors, Business Process Management Workshops - BPM 2023 International Workshops, Utrecht, The Netherlands, September 11-15, 2023, Revised Selected Papers, volume 492 of Lecture Notes in Business Information Processing, pages 453–465. Springer, 2023.
- PNML framework: An extendable reference implementation of the petri net markup language. In Johan Lilius and Wojciech Penczek, editors, Applications and Theory of Petri Nets, 31st International Conference, PETRI NETS 2010, Braga, Portugal, June 21-25, 2010. Proceedings, volume 6128 of Lecture Notes in Computer Science, pages 318–327. Springer, 2010.
- Business process modeling: Current issues and future challenges. In Pascal van Eck, Jaap Gordijn, and Roel J. Wieringa, editors, Advanced Information Systems Engineering, 21st International Conference, CAiSE 2009, Amsterdam, The Netherlands, June 8-12, 2009. Proceedings, volume 5565 of Lecture Notes in Computer Science, pages 501–514. Springer, 2009.
- Dehallucinating large language models using formal methods guided iterative prompting. In IEEE International Conference on Assured Autonomy, ICAA 2023, Laurel, MD, USA, June 6-8, 2023, pages 149–152. IEEE, 2023.
- Conversational process modelling: State of the art, applications, and implications in practice. In Chiara Di Francescomarino, Andrea Burattin, Christian Janiesch, and Shazia W. Sadiq, editors, Business Process Management Forum - BPM 2023 Forum, Utrecht, The Netherlands, September 11-15, 2023, Proceedings, volume 490 of Lecture Notes in Business Information Processing, pages 319–336. Springer, 2023.
- Humam Kourani and Sebastiaan J. van Zelst. POWL: partially ordered workflow language. In Chiara Di Francescomarino, Andrea Burattin, Christian Janiesch, and Shazia Sadiq, editors, Business Process Management - 21st International Conference, BPM 2023, Utrecht, The Netherlands, September 11-15, 2023, Proceedings, volume 14159 of Lecture Notes in Computer Science, pages 92–108. Springer, 2023.
- Scalable discovery of partially ordered workflow models with formal guarantees. In 5th International Conference on Process Mining, ICPM 2023, Rome, Italy, October 23-27, 2023, pages 89–96. IEEE, 2023.
- Sander J. J. Leemans. Robust Process Mining with Guarantees - Process Discovery, Conformance Checking and Enhancement, volume 440 of Lecture Notes in Business Information Processing. Springer, 2022.
- Pretrained language model for text generation: A survey. In Zhi-Hua Zhou, editor, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21, pages 4492–4499. International Joint Conferences on Artificial Intelligence Organization, 8 2021. Survey Track.
- Parameter-efficient sparsity for large language models fine-tuning. In Luc De Raedt, editor, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI 2022, Vienna, Austria, 23-29 July 2022, pages 4223–4229. ijcai.org, 2022.
- OpenAI. GPT-4 technical report. CoRR, abs/2303.08774, 2023.
- SPDF: sparse pre-training and dense fine-tuning for large language models. In Robin J. Evans and Ilya Shpitser, editors, Uncertainty in Artificial Intelligence, UAI 2023, July 31 - 4 August 2023, Pittsburgh, PA, USA, volume 216 of Proceedings of Machine Learning Research, pages 2134–2146. PMLR, 2023.
- A composable just-in-time programming framework with llms and FBP. In IEEE High Performance Extreme Computing Conference, HPEC 2023, Boston, MA, USA, September 25-29, 2023, pages 1–8. IEEE, 2023.
- Large language models for business process management: Opportunities and challenges. In Chiara Di Francescomarino, Andrea Burattin, Christian Janiesch, and Shazia W. Sadiq, editors, Business Process Management Forum - BPM 2023 Forum, Utrecht, The Netherlands, September 11-15, 2023, Proceedings, volume 490 of Lecture Notes in Business Information Processing, pages 107–123. Springer, 2023.
- Business process model and notation - BPMN. In Mark von Rosing, Henrik von Scheel, and August-Wilhelm Scheer, editors, The Complete Business Process Handbook: Body of Knowledge from Process Modeling to BPM, Volume I, pages 429–453. Morgan Kaufmann/Elsevier, 2015.
- Expertprompting: Instructing large language models to be distinguished experts. CoRR, abs/2305.14688, 2023.
- Least-to-most prompting enables complex reasoning in large language models. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net, 2023.
- Large language models are human-level prompt engineers. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023. OpenReview.net, 2023.