GANDR：可验证法律答案生成中的声明审核
GANDR: Claim Auditing for Verifiable Legal Answer Generation
GANDR系统让法律AI答案的每个声明都可验证，准确率比现有系统高11个百分点，代码已开源。
GANDR是一个双智能体系统，由起草者以结构化法律推理格式撰写答案，审核者独立验证每个声明与引用来源的匹配度。
在185项法律基准测试中，GANDR达到70.8%的严格准确率，领先最强基线11.
3个百分点。系统采用协议锚定提交规则，移除后准确率下降22.
7个百分点。审核者对不充分声明的二分类检测F1值为0.
84。
GANDR: Claim Auditing for Verifiable Legal Answer Generation
In high-stakes domains such as legal practice, a language-model answer is only useful to the extent that a reader can verify each claim against the source the system cites. Current grounded-generation pipelines score the answer as a whole, so a correct conclusion can rest on fabricated or loosely matched citations and still score well. Closing this gap requires both a system built for per-claim verification and an evaluation that measures it. We introduce GANDR (Grounded ANswer DRafter), a two-agent system in which a Drafter writes an answer in a structured legal-reasoning format and a separate Critic, with the same view as a human verifier, audits each claim against its cited source and emits a per-claim audit trace on every round. We pair it with a strict correctness criterion requiring every citation to resolve to a passage the retriever returned. On a 185-item legal benchmark where all six systems share one backbone, one retrieval surface, and one citation instruction, GANDR ranks first on every primary metric, reaching 70.8% strict accuracy and leading the strongest baseline by 11.3 points (p<0.01). Reverting the protocol-anchored commit rule lowers strict accuracy by 22.7 points, and the strict lead stays positive on three further backbones, at +3.2 to +6.5 points. This lead traces to the Drafter configuration and the protocol-anchored commit, not to rewriting. Against two law-trained annotators the audit flags under-supported claims at F1 0.84 as a binary detector, while its four-way verdict labels agree only weakly and are advisory. Code is available upon request.
本条情报归属 AITOP「论文」核心栏目，重点聚焦北美前沿实验室与硅谷科技巨头。在跨区域产业观察坐标中，该动态直接关联「AI 开发者工具链、Coding Agent 与工程化实践」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：GANDR、法律AI、可验证生成、声明审核，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。
信源核验说明：本文原始线索采编自「arXiv cs.AI」（@Chen Qian, Yimeng Wang, Yu Chen, Lingfei Wu, Andreas Stathopoulos），经 AITOP 多维评分管线结构化提炼。