LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law

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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.

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Santosh, T. Y. S. S., Aly, M., Ichim, O., & Grabmair, M. (2025). LexGenie: Automated Generation of Structured Reports for European Court of Human Rights Case Law. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 6, pp. 672–683). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.acl-industry.47

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