Applicability of large language models and generative models for legal case judgement summarization

Author:

Deroy AniketORCID,Ghosh Kripabandhu,Ghosh Saptarshi

Publisher

Springer Science and Business Media LLC

Reference50 articles.

1. Ahmad M, Yaramic I, Roy TD (2023) Creating trustworthy llms: dealing with hallucinations in healthcare ai

2. Ahmed T, Devanbu P (2023) Few-shot training llms for project-specific code-summarization. In: Proceedings of the 37th IEEE/ACM international conference on automated software engineering

3. Banerjee S, Lavie A (2005) Meteor: an automatic metric for mt evaluation with improved correlation with human judgments. In: Proceedings of the ACL workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization, pp 65–72

4. Beltagy I, Peters ME, Cohan A (2020) Longformer: the long-document transformer. arXiv preprint arXiv:2004.05150

5. Bhattacharya P, Hiware K, Rajgaria S, Pochhi N, Ghosh K, Ghosh S (2019) A comparative study of summarization algorithms applied to legal case judgments. In: Proceedings of european conference on information retrieval (ECIR), pp. 413–428

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