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English(EN) AxQM: A Textbook-Scale Benchmark for Formal Proof Synthesis in a Library of Finite-Dimensional Quantum Mechanics

新基准AxQM测试LLM形式化量子力学能力

研究人员推出了AxQM,一个旨在评估大型语言模型在物理学形式化能力的新基准。该基准包含一千多个来自Nielsen和Chuang合著的教科书《量子计算与量子信息》的证明合成任务。AxQM是使用一个定制的有限维量子力学Lean库构建的,旨在成为目前最大的物理学证明合成基准,其任务数量是先前基准的四倍。该基准确保每个任务都有可验证的解决方案,并由Lean内核进行评分,以确认证明编译和未解析声明的缺失。 AI

影响 该基准有望加速在科学领域进行严格形式化的人工智能系统的开发。

排序理由 该集群描述了一个新的物理学形式化证明合成基准,该基准基于一本教科书并使用证明助手。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新基准AxQM测试LLM形式化量子力学能力

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该集群描述了一个新的物理学形式化证明合成基准,该基准基于一本教科书并使用证明助手。[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) · Weichen Winston Yin, Jacob M. Taylor, Dirk R. Englund, Frank H. L. Koppens ·

    AxQM:一个用于有限维量子力学库中形式证明合成的教科书规模基准

    arXiv:2609.05157v1 Announce Type: cross Abstract: Formalizing mathematics in a proof assistant, where a machine checks every definition, statement and proof, has set a new standard of rigor. Large language models are now capable of formalizing autonomously, even at the scale of w…