Papers with Legal NLP
Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation (2022.aacl-main)
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Abhay Shukla, Paheli Bhattacharya, Soham Poddar, Rajdeep Mukherjee, Kripabandhu Ghosh, Pawan Goyal, Saptarshi Ghosh
| Challenge: | Summarization of legal case judgement documents is a challenging problem in Legal NLP. |
| Approach: | They propose to use extractive and abstractive summarization methods to evaluate legal document summarizing systems. |
| Outcome: | The proposed methods have been evaluated on three legal summarization datasets. |
ILSIC: Corpora for Identifying Indian Legal Statutes from Queries by Laymen (2026.findings-eacl)
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| Challenge: | Existing studies have focused on the use of court judgments as input for legal Statute Identification (LSI) however, there is little research to explore the differences between court and laypeople data for LSI. |
| Approach: | They create a corpus of laypeople queries covering 500+ statutes from Indian law . they use court case judgements to compare between the two datasets . |
| Outcome: | The proposed corpus of laypeople queries covers 500+ statutes from Indian law . the results show that models trained on court judgements are ineffective . |
BriefMe: A Legal NLP Benchmark for Assisting with Legal Briefs (2025.findings-acl)
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| Challenge: | a core part of legal work that has been underexplored in Legal NLP is the writing and editing of legal briefs. |
| Approach: | They propose to use large language models to help legal professionals with writing briefs by capturing and evaluating their abilities in language models. |
| Outcome: | The proposed tasks show that the models perform well on arguments summarization, argument completion, and case retrieval tasks. |