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ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining

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arxiv 2209.01650 v2 pith:7ONJQE7Z submitted 2022-09-04 cs.CL

Mohamed Elaraby , Diane Litman This is my paper · ORCID
classification cs.CL
keywords documentslegalargumentargumentativesummarizationabilityabstractiveaddress
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A challenging task when generating summaries of legal documents is the ability to address their argumentative nature. We introduce a simple technique to capture the argumentative structure of legal documents by integrating argument role labeling into the summarization process. Experiments with pretrained language models show that our proposed approach improves performance over strong baselines

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  1. A Comprehensive Survey on Legal Summarization: Challenges and Future Directions

    cs.CL 2025-01 conditional novelty 4.0 of 10

    A systematic survey of legal summarization finds a field dominated by English common-law datasets, ROUGE-based evaluation, and few human or expert validation studies.

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