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Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking

2023-06-01Code Available0· sign in to hype

Mohamed Elaraby, Yang Zhong, Diane Litman

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Abstract

We propose a simple approach for the abstractive summarization of long legal opinions that considers the argument structure of the document. Legal opinions often contain complex and nuanced argumentation, making it challenging to generate a concise summary that accurately captures the main points of the legal opinion. Our approach involves using argument role information to generate multiple candidate summaries, then reranking these candidates based on alignment with the document's argument structure. We demonstrate the effectiveness of our approach on a dataset of long legal opinions and show that it outperforms several strong baselines.

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