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Legal judgment prediction (LJP) applies Natural Language Processing (NLP) techniques to predict judgment results based on fact descriptions automatically.
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2018
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doi:10.18653/v1/D18-1390
H. Zhong, Z. Guo, C. Tu, C. Xiao, Z. Liu, M. Sun, Legal judgment prediction via topological learning , in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Brussels, Belgium, 2018, pp. 3540–3549 · 2018
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H. Ye, X. Jiang, Z. Luo, W. Chao, Interpretable charge predictions for criminal cases: Learning to generate court views from fact descriptions, NAACL-HLT (2018)
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K. Kowsrihawat, P. Vateekul, P. Boonkwan, Predicting judicial decisions of criminal cases from thai supreme court using bi-directional gru with attention mechanism, in: 2018 5th Asian Conference on Defense Technology (ACDT), IEEE, 2018, pp. 50–55
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M. Medvedeva, M. Vols, M. Wieling, Judicial decisions of the european court of human rights: Looking into the crystal ball, in: Proceedings of of the Conference on Empirical Legal Studies, 2018, pp. 1–24
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P. Wang, Z. Yang, S. Niu, Y. Zhang, S. Z. Niu, Modeling dynamic pairwise attention for crime classification over legal articles (2018) · 2018
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Z. Hu, X. Li, C. Tu, Z. Liu, M. Sun, Few-shot charge prediction with discriminative legal attributes , in: Proceedings of the 27th International Conference on Computational Linguistics, Association for Computational Linguistics, Santa Fe, New Mexico, USA, 2018, pp. 487–498. URL https://aclanthology.org/C18-1041
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Y. Zhao, X. Shen, H. Senuma, A. Aizawa, A comprehensive study: Sentence compression with linguistic knowledge-enhanced gated neural network, Data & Knowledge Engineering 117 (2018) 307–318
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R. A. Oppel Jr, J. K. Patel, One lawyer, 194 felony cases, and no time, New York Times 31 (2019)
2019
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doi:10.18653/v1/N19-1423
J. Devlin, M.-W. Chang, K. Lee, K. Toutanova, BERT: Pre-training of deep bidirectional transformers for language understanding , in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), Association for Computational Linguistics, Minneapolis, Minnesota, 2019, pp. 4171–4186 · 2019
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M. Zaheer, G. Guruganesh, K. A. Dubey, J. Ainslie, C. Alberti, S. Ontanon, P. Pham, A. Ravula, Q. Wang, L. Yang, et al., Big bird: Transformers for longer sequences, Advances in Neural Information Processing Systems 33 (2020) 17283–17297
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H. J. Spaeth, L. Epstein, J. A. Segal, A. D. Martin, S. C. Ruger, Theodore J.and Benesh, Supreme court database, version 2020 release 01. washington university law., URL: http://supremecourtdatabase.org/ (2020)
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D. Tuggener, P. von Däniken, T. Peetz, M. Cieliebak, Ledgar: a large-scale multi-label corpus for text classification of legal provisions in contracts, in: 12th Language Resources and Evaluation Conference (LREC) 2020, European Language Resources Association, 2020, pp. 1228–1234
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Y. Wu, K. Kuang, Y. Zhang, X. Liu, C. Sun, J. Xiao, Y. Zhuang, L. Si, F. Wu, De-biased court’s view generation with causality , in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), Association for Computational Linguistics, Online, 2020, pp. 763–780 · 2020
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2019
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2019
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K. Ligeti, The place of the prosecutor in common law and civil law jurisdictions, The Oxford Handbook of Criminal Process (2019)
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doi:10.1007/978-981-15-1377-0_59
S. Pan, T. Lu, N. Gu, H. Zhang, C. Xu, Charge Prediction for Multi-defendant Cases with Multi-scale Attention, Communications in Computer and Information Science, Springer Singapore, 2019, book section Chapter 59, pp. 766–777 · 2019
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2019
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S. Long, C. Tu, Z. Liu, M. Sun, Automatic judgment prediction via legal reading comprehension, in: China National Conference on Chinese Computational Linguistics, Springer, 2019, pp. 558–572
2019
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2019
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H. Su, X. Shen, S. Zhao, Z. Xiao, P. Hu, R. Zhong, C. Niu, J. Zhou, Diversifying dialogue generation with non-conversational text, in: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020, pp. 7087–7097
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H. Su, X. Shen, Z. Xiao, Z. Zhang, E. Chang, C. Zhang, C. Niu, J. Zhou, Moviechats: Chat like humans in a closed domain, in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020, pp. 6605–6619
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E. Chang, J. Caplinger, A. Marin, X. Shen, V. Demberg, Dart: A lightweight quality-suggestive data-to-text annotation tool, in: Proceedings of the 28th International Conference on Computational Linguistics: System Demonstrations, 2020, pp. 12–17
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B. Xu, S. Qiu, J. Zhang, Y. Wang, X. Shen, G. de Melo, Data augmentation for multiclass utterance classification–a systematic study, in: Proceedings of the 28th International Conference on Computational Linguistics, 2020, pp. 5494–5506
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H. C. N. J. Data, National judicial data grid (district and taluka courts of india) (2021)
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P. Kalamkar, et al., Indian legal nlp benchmarks: A survey, arXiv preprint arXiv:2107.06056 (2021)
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I. Chalkidis, A. Jana, D. Hartung, M. J. Bommarito, I. Androutsopoulos, D. M. Katz, N. Aletras, Lexglue: A benchmark dataset for legal language understanding in english, Available at SSRN 3936759 (2021)
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C. Xiao, X. Hu, Z. Liu, C. Tu, M. Sun, Lawformer: A pre-trained language model for chinese legal long documents, AI Open (2021)
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L. Ma, Y. Zhang, T. Wang, X. Liu, S. Zhang, Legal judgment prediction with multi-stage case representation learning in the real court setting (2021) · 2021
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P. Bambroo, A. Awasthi, Legaldb: Long distilbert for legal document classification, in: 2021 International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), IEEE, 2021, pp. 1–4
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E. Chang, X. Shen, D. Zhu, V. Demberg, H. Su, Neural data-to-text generation with lm-based text augmentation, in: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021, pp. 758–768
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E. Chang, X. Shen, H.-S. Yeh, V. Demberg, On training instance selection for few-shot neural text generation, in: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), 2021, pp. 8–13
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X. Jiang, H. Ye, Z. Luo, W. Chao, W. Ma, Interpretable rationale augmented charge prediction system , in: Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, Association for Computational Linguistics, Santa Fe, New Mexico, 2018, pp. 146–151. URL https://aclanthology.org/C18-2032
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