Case Retrieval for Legal Judgment Prediction in Legal Artificial Intelligence

Zhang Han, Dou Zhicheng

Abstract
“Legal judgment prediction (LJP) is a basic task in legal artificial intelligence. It consists ofthree subtasks, which are relevant law article prediction, charge prediction and term of penaltyprediction, and gives the judgment results to assist the work of judges. In recent years, many deeplearning methods have emerged to improve the performance of the legal judgment prediction task. The previous methods mainly improve the performance by integrating law articles and the factdescription of a legal case. However, they rarely consider that the judges usually look up historicalcases before making a judgment in the actual scenario. To simulate this scenario, we propose ahistorical case retrieval framework for the legal judgment prediction task. Specifically, we selectsome historical cases which include all categories from the training dataset. Then, we retrieve themost similar Top-k historical cases of the current legal case and use the vector representation ofthese Top-k historical cases to help predict the judgment results. On two real-world legal datasets,our model achieves better results than several state-of-the-art baseline models.”
Anthology ID:
2023.ccl-1.68
Volume:
Proceedings of the 22nd Chinese National Conference on Computational Linguistics
Month:
August
Year:
2023
Address:
Harbin, China
Editors:
Maosong Sun, Bing Qin, Xipeng Qiu, Jing Jiang, Xianpei Han
Venue:
CCL
SIG:
Publisher:
Chinese Information Processing Society of China
Note:
Pages:
801–812
Language:
English
URL:
https://aclanthology.org/2023.ccl-1.68
DOI:
Bibkey:
Cite (ACL):
Zhang Han and Dou Zhicheng. 2023. Case Retrieval for Legal Judgment Prediction in Legal Artificial Intelligence. In Proceedings of the 22nd Chinese National Conference on Computational Linguistics, pages 801–812, Harbin, China. Chinese Information Processing Society of China.
Cite (Informal):
Case Retrieval for Legal Judgment Prediction in Legal Artificial Intelligence (Han & Zhicheng, CCL 2023)
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