Year: 2025
Type: article
Study design: Systematic Review
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.
Source: ACM Computing Surveys
DOI: 10.1145/3776586
Authors: Mousumi Akter, Erion Çano, Erik Weber, Dennis Dobler, Ivan Habernal
Institutions: TU Dortmund University, Ruhr University Bochum
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4416522876