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Bibliographic Details
Main Authors: Akter, Mousumi, Çano, Erion, Weber, Erik, Dobler, Dennis, Habernal, Ivan
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2501.17830
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Table of Contents:
  • 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.