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arXiv · 2607.11109

Generative Chinese Statute Retrieval

Yiteng Tu·Zitao Su·Weihang Su·Xuanyi Chen·Yueyue Wu·Yiqun Liu·Min Zhang·Qingyao Ai
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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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Yiteng Tu, Zitao Su, Weihang Su, Xuanyi Chen, Yueyue Wu, Yiqun Liu, Min Zhang, Qingyao Ai. 2026-07-13. Generative Chinese Statute Retrieval. https://arxiv.org/abs/2607.11109

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