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Given the fact of a case, Legal Judgment Prediction (LJP) involves a series of sub-tasks such as predicting violated law articles, charges and term of penalty.
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2018
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H. Zhong, Z. Guo, C. Tu, C. Xiao, Z. Liu, and M. Sun, “Legal Judgment Prediction via Topological Learning,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Brussels, Belgium: Association for Computational Linguistics, 2018, pp. 3540–3549
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2020
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P. Wang, Z. Yang, S. Niu, Y. Zhang, L. Zhang, and S. Niu, “Modeling dynamic pairwise attention for crime classification over legal articles,” in The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval , 2018, pp. 485–494
2018
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S. Long, C. Tu, Z. Liu, and M. Sun, “Automatic Judgment Prediction via Legal Reading Comprehension,” in Chinese Computational Linguistics , ser. Lecture Notes in Computer Science, M. Sun, X. Huang, H. Ji, Z. Liu, and Y. Liu, Eds. Cham: Springer International Publishing, 2019, pp. 558–572
2019
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H. Chen, D. Cai, W. Dai, Z. Dai, and Y. Ding, “Charge-Based Prison Term Prediction with Deep Gating Network,” in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Hong Kong, China: Association for Computational Linguistics, Nov. 2019, pp. 6362–6367
2019
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W. Yang, W. Jia, X. Zhou, and Y. Luo, “Legal Judgment Prediction via Multi-Perspective Bi-Feedback Network,” in Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence . Macao, China: International Joint Conferences on Artificial Intelligence Organization, Aug. 2019, pp. 4085–4091
2019
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H. Zhong, Z. Zhang, Z. Liu, and M. Sun, “Open Chinese Language Pre-trained Model Zoo,” Tech. Rep., 2019. [Online]. Available: https://github.com/thunlp/openclap
2019
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2019
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I. Chalkidis, E. Fergadiotis, P. Malakasiotis, and I. Androutsopoulos, “Large-Scale Multi-Label Text Classification on EU Legislation,” in Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics . Florence, Italy: Association for Computational Linguistics, Jul. 2019, pp. 6314–6322
2019
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C. He, L. Peng, Y. Le, J. He, and X. Zhu, “SECaps: A Sequence Enhanced Capsule Model for Charge Prediction,” in Artificial Neural Networks and Machine Learning – ICANN 2019: Text and Time Series , ser. Lecture Notes in Computer Science, I. V. Tetko, V. Kůrková, P. Karpov, and F. Theis, Eds. Cham: Springer International Publishing, 2019, pp. 227–239
2019
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Z. Yang, P. Wang, L. Zhang, L. Shou, and W. Xu, “A recurrent attention network for judgment prediction,” in International Conference on Artificial Neural Networks . Springer, 2019, pp. 253–266
2019
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2020
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2020
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2020
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2020
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2020
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T. Schick and H. Schütze, “It’s not just size that matters: Small language models are also few-shot learners,” in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies , 2021, pp. 2339–2352
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