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        <title>Legal Case Retrieval: A Survey of the State of the Art</title>
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    <abstract>Recent years have seen increasing attention on Legal Case Retrieval (LCR), a key task in the area of Legal AI that concerns the retrieval of cases from a large legal database of historical cases that are similar to a given query. This paper presents a survey of the major milestones made in LCR research, targeting researchers who are finding their way into the field and seek a brief account of the relevant datasets and the recent neural models and their performances.</abstract>
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%0 Conference Proceedings
%T Legal Case Retrieval: A Survey of the State of the Art
%A Feng, Yi
%A Li, Chuanyi
%A Ng, Vincent
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F feng-etal-2024-legal
%X Recent years have seen increasing attention on Legal Case Retrieval (LCR), a key task in the area of Legal AI that concerns the retrieval of cases from a large legal database of historical cases that are similar to a given query. This paper presents a survey of the major milestones made in LCR research, targeting researchers who are finding their way into the field and seek a brief account of the relevant datasets and the recent neural models and their performances.
%U https://aclanthology.org/2024.acl-long.350
%P 6472-6485

Markdown (Informal)

[Legal Case Retrieval: A Survey of the State of the Art](https://aclanthology.org/2024.acl-long.350) (Feng et al., ACL 2024)

• Legal Case Retrieval: A Survey of the State of the Art (Feng et al., ACL 2024)

ACL

• Yi Feng, Chuanyi Li, and Vincent Ng. 2024. Legal Case Retrieval: A Survey of the State of the Art. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 6472–6485, Bangkok, Thailand. Association for Computational Linguistics.