Few-Shot Learning for Chinese Legal Controversial Issues Classification

Author:

Fang YinORCID,Tian XinORCID,Wu HaoORCID,Gu SongyuanORCID,Wang ZhuORCID,Wang FengORCID,Li JunliangORCID,Weng YangORCID

Funder

National Basic Research Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Tagging Items with Emerging Tags: A Neural Topic Model Based Few-Shot Learning Approach;ACM Transactions on Information Systems;2024-03-22

2. A topic discovery approach for unsupervised organization of legal document collections;Artificial Intelligence and Law;2023-07-19

3. Topic Term Clustering Based on Semi-supervised Co-occurrence Graph and Its Application in Chinese Judgement Documents;Computer Science and Education;2023

4. Organizing Portuguese Legal Documents through Topic Discovery;Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval;2022-07-06

5. A Comparison Study of Pre-trained Language Models for Chinese Legal Document Classification;2022 5th International Conference on Artificial Intelligence and Big Data (ICAIBD);2022-05-27

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