ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining

• URL: http://arxiv.org/abs/2209.01650v1
• Date: Sun, 4 Sep 2022 15:55:56 GMT
• Title: ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining
• Authors: Mohamed Elaraby, Diane Litman
• Abstract summary: We introduce a 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.
• Score: 0.2538209532048867
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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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