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English(EN) Verifiable LLM-Guided Focal SMT Solving for Quantified Arrays

LLM 指导 SMT 求解器解决复杂逻辑问题

研究人员开发了 LinguaArray,一个利用大型语言模型 (LLM) 来指导形式推理系统解决复杂问题的新框架,特别是在量化数组 SMT(可满足性模理论)求解方面。虽然 LLM 不能直接用于生成证明,但 LinguaArray 利用它们来识别关键的语义结构,提出一小组焦点地面项或约束。然后,传统的 SMT 求解器会验证这些建议,确保所有结果都由求解器本身认证。这种方法显著增强了求解器的能力,使其能够处理在给定时间限制内否则无法解决的实例。 AI

影响 通过将 LLM 的见解与认证的求解器输结合,增强了形式验证能力。

排序理由 学术论文,详细介绍了 LLM 指导的形式推理新框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

LLM 指导 SMT 求解器解决复杂逻辑问题

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学术论文,详细介绍了 LLM 指导的形式推理新框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Kunhang Lv, Rui Han, Fuqi Jia, Yuhang Dong, Feifei Ma, Jian Zhang ·

    可验证的LLM引导的量化数组焦点SMT求解

    arXiv:2610.39435v1 Announce Type: new Abstract: Large language models can often identify useful semantic structure in formal artifacts, but their outputs cannot be trusted as proofs or solver decisions. We study whether LLMs can instead guide formal reasoning systems through a na…