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arXiv · 2501.17830

A Comprehensive Survey on Legal Summarization: Challenges and Future Directions

Mousumi Akter·Erion Çano·Erik Weber·Dennis Dobler·Ivan Habernal
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Abstract

This article provides a systematic up-to-date survey of automatic summarization techniques, datasets, models, and evaluation methods in the legal domain. Through specific source selection criteria, we thoroughly review over 120 papers spanning the modern `transformer' era of natural language processing (NLP), thus filling a gap in existing systematic surveys on the matter. We present existing research along several axes and discuss trends, challenges, and opportunities for future research.

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Mousumi Akter, Erion Çano, Erik Weber, Dennis Dobler, Ivan Habernal. 2025-01-29. A Comprehensive Survey on Legal Summarization: Challenges and Future Directions. https://arxiv.org/abs/2501.17830

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