What to Read in a Contract? Party-Specific Summarization of Legal Obligations, Entitlements, and Prohibitions
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Abstract (arXiv)
Reviewing and comprehending key obligations, entitlements, and prohibitions in legal contracts can be a tedious task due to their length and domain-specificity. Furthermore, the key rights and duties requiring review vary for each contracting party. In this work, we propose a new task of party-specific extractive summarization for legal contracts to facilitate faster reviewing and improved comprehension of rights and duties. To facilitate this, we curate a dataset comprising of party-specific pairwise importance comparisons annotated by legal experts, covering ~293K sentence pairs that include obligations, entitlements, and prohibitions extracted from lease agreements. Using this dataset, we train a pairwise importance ranker and propose a pipeline-based extractive summarization system that generates a party-specific contract summary. We establish the need for incorporating domain-specific notion of importance during summarization by comparing our system against various baselines using both automatic and human evaluation methods
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 15 of its 51 references that are in the map. First posted on arXiv 19 Dec 2022.
Builds on
15 of 51 references.
References · 15
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Citing papers per year: 2024: 3; 2025: 1; 2026: 1.
5 papers.
- 2024LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in Englishcited by 7
- 2025A Comprehensive Survey on Legal Summarization: Challenges and Future Directionscited by 6
- 2024How Private are Language Models in Abstractive Summarization?cited by 2
- 2024A Survey on the Real Power of ChatGPTcited by 0
- 2026ContraVis: Evidence-Grounded Visual Analytics for Contradiction Review in Legal Contractscited by 0
- 2026ContraVis: Evidence-Grounded Visual Analytics for Contradiction Review in Legal Contracts22 Sep 2026
- 2025A Comprehensive Survey on Legal Summarization: Challenges and Future Directions29 Jan 2025
- 2024How Private are Language Models in Abstractive Summarization?16 Dec 2024
- 2024LexSumm and LexT5: Benchmarking and Modeling Legal Summarization Tasks in English12 Oct 2024
- 2024A Survey on the Real Power of ChatGPT22 Apr 2024