@inproceedings{t-y-s-s-etal-2025-lexgenie,
title = "{L}ex{G}enie: Automated Generation of Structured Reports for {E}uropean Court of Human Rights Case Law",
author = "T.y.s.s, Santosh and
Aly, Mahmoud and
Ichim, Oana and
Grabmair, Matthias",
editor = "Rehm, Georg and
Li, Yunyao",
booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.acl-industry.47/",
doi = "10.18653/v1/2025.acl-industry.47",
pages = "672--683",
ISBN = "979-8-89176-288-6",
abstract = "Analyzing large volumes of case law to uncover evolving legal principles, across multiple cases, on a given topic is a demanding task for legal professionals. Structured topical reports provide an effective solution by summarizing key issues, principles, and judgments, enabling comprehensive legal analysis on a particular topic. While prior works have advanced query-based individual case summarization, none have extended to automatically generating multi-case structured reports. To address this, we introduce LexGenie, an automated LLM-based pipeline designed to create structured reports using the entire body of case law on user-specified topics within the European Court of Human Rights jurisdiction. LexGenie retrieves, clusters, and organizes relevant passages by topic to generate a structured outline and cohesive content for each section. Expert evaluation confirms LexGenie{'}s utility in producing structured reports that enhance efficient, scalable legal analysis."
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<abstract>Analyzing large volumes of case law to uncover evolving legal principles, across multiple cases, on a given topic is a demanding task for legal professionals. Structured topical reports provide an effective solution by summarizing key issues, principles, and judgments, enabling comprehensive legal analysis on a particular topic. While prior works have advanced query-based individual case summarization, none have extended to automatically generating multi-case structured reports. To address this, we introduce LexGenie, an automated LLM-based pipeline designed to create structured reports using the entire body of case law on user-specified topics within the European Court of Human Rights jurisdiction. LexGenie retrieves, clusters, and organizes relevant passages by topic to generate a structured outline and cohesive content for each section. Expert evaluation confirms LexGenie’s utility in producing structured reports that enhance efficient, scalable legal analysis.</abstract>
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%0 Conference Proceedings
%T LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law
%A T.y.s.s, Santosh
%A Aly, Mahmoud
%A Ichim, Oana
%A Grabmair, Matthias
%Y Rehm, Georg
%Y Li, Yunyao
%S Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-288-6
%F t-y-s-s-etal-2025-lexgenie
%X Analyzing large volumes of case law to uncover evolving legal principles, across multiple cases, on a given topic is a demanding task for legal professionals. Structured topical reports provide an effective solution by summarizing key issues, principles, and judgments, enabling comprehensive legal analysis on a particular topic. While prior works have advanced query-based individual case summarization, none have extended to automatically generating multi-case structured reports. To address this, we introduce LexGenie, an automated LLM-based pipeline designed to create structured reports using the entire body of case law on user-specified topics within the European Court of Human Rights jurisdiction. LexGenie retrieves, clusters, and organizes relevant passages by topic to generate a structured outline and cohesive content for each section. Expert evaluation confirms LexGenie’s utility in producing structured reports that enhance efficient, scalable legal analysis.
%R 10.18653/v1/2025.acl-industry.47
%U https://aclanthology.org/2025.acl-industry.47/
%U https://doi.org/10.18653/v1/2025.acl-industry.47
%P 672-683
Markdown (Informal)
[LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law](https://aclanthology.org/2025.acl-industry.47/) (T.y.s.s et al., ACL 2025)
ACL