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CitaLaw: Enhancing LLM with Citations in Legal Domain

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arxiv 2412.14556 v2 pith:V6AH6KCR submitted 2024-12-19 cs.CL

CitaLaw: Enhancing LLM with Citations in Legal Domain

classification cs.CL
keywords citationslegalcitalawresponsescorpusevaluationllmsquestions
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In this paper, we propose CitaLaw, the first benchmark designed to evaluate LLMs' ability to produce legally sound responses with appropriate citations. CitaLaw features a diverse set of legal questions for both laypersons and practitioners, paired with a comprehensive corpus of law articles and precedent cases as a reference pool. This framework enables LLM-based systems to retrieve supporting citations from the reference corpus and align these citations with the corresponding sentences in their responses. Moreover, we introduce syllogism-inspired evaluation methods to assess the legal alignment between retrieved references and LLM-generated responses, as well as their consistency with user questions. Extensive experiments on 2 open-domain and 7 legal-specific LLMs demonstrate that integrating legal references substantially enhances response quality. Furthermore, our proposed syllogism-based evaluation method exhibits strong agreement with human judgments.

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