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Legal case retrieval techniques play an essential role in modern intelligent legal systems.
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Building legal case retrieval systems with lexical matching and summarization using a pre-trained phrase scoring model. In Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law . 275–282
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COLIEE 2020: methods for legal document retrieval and entailment. In JSAI International Symposium on Artificial Intelligence . Springer, 196–210
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BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case Retrieval.. In IJCAI . 3501–3507
Yunqiu Shao, Jiaxin Mao, Yiqun Liu, Weizhi Ma, Ken Satoh, Min Zhang, and Shaoping Ma. 2020 · 2020
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RepBERT: Contextualized text embeddings for first-stage retrieval
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Min Zhang, and Shaoping Ma. 2020 · 2020
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Sophia Althammer, Arian Askari, Suzan Verberne, and Allan Hanbury. 2021 · 2021
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Retrieving legal cases from a large-scale candidate corpus
Pre-training methods in information retrieval
Yixing Fan, Xiaohui Xie, Yinqiong Cai, Jia Chen, Xinyu Ma, Xiangsheng Li, Ruqing Zhang, Jiafeng Guo, et al · 2022
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Case law retrieval: problems, methods, challenges and evaluations in the last 20 years
Daniel Locke and Guido Zuccon. 2022 · 2022
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Overview and Discussion of the Competition on Legal Information Extraction/Entailment (COLIEE) 2021
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THUIR at the NTCIR-16 WWW-4 Task
Shenghao Yang, Haitao Li, Zhumin Chu, Jingtao Zhan, Yiqun Liu, Min Zhang, and Shaoping Ma. 2022 · 2022
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Explainable legal case matching via inverse optimal transport-based rationale extraction. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 657–668
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Yixiao Ma, Yunqiu Shao, Bulou Liu, Yiqun Liu, Min Zhang, and Shaoping Ma. 2021a · 2021
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RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . 5835–5847
Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Wayne Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2021 · 2021
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Lawformer: A pre-trained language model for chinese legal long documents
Chaojun Xiao, Xueyu Hu, Zhiyuan Liu, Cunchao Tu, and Maosong Sun. 2021 · 2021
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Optimizing dense retrieval model training with hard negatives. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1503–1512
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, and Shaoping Ma. 2021 · 2021
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Axiomatically Regularized Pre-training for Ad hoc Search
Jia Chen, Yiqun Liu, Yan Fang, Jiaxin Mao, Hui Fang, Shenghao Yang, Xiaohui Xie, Min Zhang, and Shaoping Ma. 2022 · 2022
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Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking
Qian Dong, Yiding Liu, Suqi Cheng, Shuaiqiang Wang, Zhicong Cheng, Shuzi Niu, and Dawei Yin. 2022 · 2022
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SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
Haitao Li, Qingyao Ai, Jia Chen, Qian Dong, Yueyue Wu, Yiqun Liu, Chong Chen, and Qi Tian. 2023a
Cited in the paper.
Constructing Tree-based Index for Efficient and Effective Dense Retrieval
Haitao Li, Qingyao Ai, Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Zheng Liu, and Zhao Cao. 2023b
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Later among the works it cites.
THUIR at WSDM Cup 2023 Task 1: Unbiased Learning to Rank
Jia Chen, Haitao Li, Weihang Su, Qingyao Ai, and Yiqun Liu. 2023 · 2023
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Towards Better Web Search Performance: Pre-training, Fine-tuning and Learning to Rank
Haitao Li, Jia Chen, Weihang Su, Qingyao Ai, and Yiqun Liu. 2023c · 2023
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CaseEncoder: A Knowledge-enhanced Pre-trained Model for Legal Case Encoding
Yixiao Ma, Yueyue Wu, Weihang Su, Qingyao Ai, and Yiqun Liu. 2023 · 2023
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Understanding Relevance Judgments in Legal Case Retrieval
Yunqiu Shao, Yueyue Wu, Yiqun Liu, Jiaxin Mao, and Shaoping Ma. 2023 · 2023
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T2Ranking: A large-scale Chinese Benchmark for Passage Ranking
Xiaohui Xie, Qian Dong, Bingning Wang, Feiyang Lv, Ting Yao, Weinan Gan, Zhijing Wu, Xiangsheng Li, Haitao Li, Yiqun Liu, et al · 2023
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