M. Mikail Demir · 2026 · arXiv
DOI: 10.48550/arXiv.2610.29961 · open-access PDF
鉴于要检查的索赔数量巨大,可验证的法律AI需要可扩展、成本效益的模型来满足法律的实际需求。系统一的决策模型是建立在大型语言模型上,但不是生成文本,而是返回每个选项的校准概率。这适合对法律权威的验证,问题关闭:给定的持有或没有。
Machine translation (Meta M2M100); the English original follows.
Given the enormous number of claims to be checked, verifiable legal AI requires scalable, cost-effective models that answer the practical needs of law. System One decision models are built on large language models but, instead of generating text, return a calibrated probability for each option. This suits the verification of legal authority, where the question is closed: a given holding, or none of them. We test whether such models abstain when the correct authority is missing. We extend CaseHOLD with an abstention condition in which the correct holding is replaced in 1,670 of 5,314 items, and
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