Generative Chinese Statute Retrieval

• URL: http://arxiv.org/abs/2607.11109v1
• Date: Mon, 13 Jul 2026 05:38:50 GMT
• Title: Generative Chinese Statute Retrieval
• Abstract summary: We propose a generative statute retrieval framework that internalizes statutory knowledge into a generative model.<n>Experiments show that GCSR consistently outperforms strong sparse, dense, and legal-domain baselines.
• Score: 35.02524712712555
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Statute retrieval is a fundamental task in legal information retrieval, yet existing approaches struggle to bridge the gap between colloquial legal queries and formal statutory language. In this paper, we propose GCSR, a generative statute retrieval framework that reformulates statute retrieval as a sequence generation problem and internalizes statutory knowledge into a generative model. Specifically, we propose a multi-granularity structured docid that encodes legal hierarchy and semantic information, together with a multi-task training strategy. Experiments show that GCSR consistently outperforms strong sparse, dense, and legal-domain baselines. Our results demonstrate the effectiveness of generative retrieval for statute retrieval and highlight its potential for broader legal information access and downstream legal reasoning tasks.

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