ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining

Elaraby, Mohamed, Litman, Diane

arXiv.org Artificial Intelligence 

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 Figure 1: Overview of our approach.

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