Legal Case Retrieval: A Survey of the State of the Art

Yi Feng, Chuanyi Li and Vincent Ng.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics, pp. 6472-6487, 2024.

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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.

BibTeX entry

@InProceedings{Feng+etal:24a,
  author = {Yi Feng and Chuanyi Li and Vincent Ng},
  title = {Legal Case Retrieval: A Survey of the State of the Art},
  booktitle = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages = {6472--6485}, 
  year = 2024}