用大模型自动解读法律概念，提升效率。
Automating Legal Interpretation with LLMs: Retrieval, Generation, and Evaluation
- 构建ATRIE框架，通过检索、生成、评估三步自动化法律解释。
- 生成结果在可读性和全面性上媲美专家，准确率略低但已可用。
- 适合法律从业者辅助工作，尤其需快速处理大量案例时。
法律解释是法律适应社会变化的关键，但对法律专业人士而言仍具挑战性，需投入大量时间与成本进行专业标注和总结。为减轻专家负担，本文提出一种自动化法律解释方法。基于判例法研究范式，设计新框架ATRIE，用于典型法律概念解释任务。ATRIE包含法律概念解释器与评估器：解释器利用大语言模型（LLMs）从过往案例中检索相关信息并生成解释；评估器则以我们提出的下游任务“法律概念蕴含”（Legal Concept Entailment）的性能变化作为解释质量的代理指标。自动化与多维度人工评估表明，其解释质量可媲美专家水平，且在全面性与可读性上更优。尽管准确性仍有小幅差距，但已能有效辅助法律从业者提升工作效率。
原文摘要 · Abstract (English)
Interpreting the law is always essential for the law to adapt to the ever-changing society. It is a critical and challenging task even for legal practitioners, as it requires meticulous and professional annotations and summarizations by legal experts, which are admittedly time-consuming and expensive to collect at scale. To alleviate the burden on legal experts, we propose a method for automated legal interpretation. Specifically, by emulating doctrinal legal research, we introduce a novel framework, ATRIE, to address Legal Concept Interpretation, a typical task in legal interpretation. ATRIE utilizes large language models (LLMs) to AuTomatically Retrieve concept-related information, Interpret legal concepts, and Evaluate generated interpretations, eliminating dependence on legal experts. ATRIE comprises a legal concept interpreter and a legal concept interpretation evaluator. The interpreter uses LLMs to retrieve relevant information from previous cases and interpret legal concepts. The evaluator uses performance changes on Legal Concept Entailment, a downstream task we propose, as a proxy of interpretation quality. Automated and multifaceted human evaluations indicate that the quality of our interpretations is comparable to those written by legal experts, with superior comprehensiveness and readability. Although there remains a slight gap in accuracy, it can already assist legal practitioners in improving the efficiency of legal interpretation.
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