Legal Judgment Prediction: A Survey of the State of the Art

Yi Feng; Chuanyi Li; Vincent Ng

IJCAI 2022poster43 citations

Legal Judgment Prediction: A Survey of the State of the Art

Abstract

Automatic legal judgment prediction (LJP) has recently received increasing attention in the natural language processing community in part because of its practical values as well as the associated research challenges. We present an overview of the major milestones made in LJP research covering multiple jurisdictions and multiple languages, and conclude with promising future research directions.

Survey Track: Natural Language Processing

BibTeX

@inproceedings{ijcai2022p765,
  title     = {Legal Judgment Prediction: A Survey of the State of the Art},
  author    = {Feng, Yi and Li, Chuanyi and Ng, Vincent},
  booktitle = {Proceedings of the Thirty-First International Joint Conference on
               Artificial Intelligence, {IJCAI-22}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Lud De Raedt},
  pages     = {5461--5469},
  year      = {2022},
  month     = {7},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2022/765},
  url       = {https://doi.org/10.24963/ijcai.2022/765},
}