[2604.06173] Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

[2604.06173] Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

arXiv - AI 3 min read

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Abstract page for arXiv paper 2604.06173: Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

Computer Science > Information Retrieval arXiv:2604.06173 (cs) [Submitted on 24 Jan 2026] Title:Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA Authors:Kyubyung Chae, Jewon Yeom, Jeongjae Park, Seunghyun Bae, Ijun Jang, Hyunbin Jin, Jinkwan Jang, Taesup Kim View a PDF of the paper titled Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA, by Kyubyung Chae and 7 other authors View PDF Abstract:Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory domains, relevant evidence is distributed across hierarchically linked documents, creating a statutory retrieval gap where conventional retrievers fail and models often hallucinate under incomplete context. We introduce SearchFireSafety, a structure- and safety-aware benchmark for statute-centric legal QA. Instantiated on fire-safety regulations as a representative case, the benchmark evaluates whether models can retrieve hierarchically fragmented evidence and safely abstain when statutory context is insufficient. SearchFireSafety adopts a dual-source evaluation framework combining real-world questions that require citation-aware retrieval and synthetic partial-context scenarios that stress-test hallucination and refusal behavior. Experiments across multiple large language models show that graph-guided retrieval substantially improves performance, but al...

Originally published on April 09, 2026. Curated by AI News.

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