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JNLP Team: Deep Learning for Legal Processing in COLIEE 2020 (2011.08071v1)

Published 4 Nov 2020 in cs.CL, cs.IR, and cs.LG

Abstract: We propose deep learning based methods for automatic systems of legal retrieval and legal question-answering in COLIEE 2020. These systems are all characterized by being pre-trained on large amounts of data before being finetuned for the specified tasks. This approach helps to overcome the data scarcity and achieve good performance, thus can be useful for tackling related problems in information retrieval, and decision support in the legal domain. Besides, the approach can be explored to deal with other domain specific problems.

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Authors (10)
  1. Ha-Thanh Nguyen (33 papers)
  2. Hai-Yen Thi Vuong (1 paper)
  3. Phuong Minh Nguyen (6 papers)
  4. Binh Tran Dang (3 papers)
  5. Quan Minh Bui (4 papers)
  6. Sinh Trong Vu (1 paper)
  7. Chau Minh Nguyen (3 papers)
  8. Vu Tran (16 papers)
  9. Ken Satoh (27 papers)
  10. Minh Le Nguyen (17 papers)
Citations (27)

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