cs.AI updates on arXiv.org 07月30日 12:12
Towards a Large Physics Benchmark
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本文介绍了一款由科学界开发用于评估、监控和引导大型语言模型在基础物理研究中发展的基准框架。框架基于科学理解和创造性的哲学概念,包含对问题正确性、难度和惊喜度的评分系统,并支持多种形式的问题。目前框架包含多种示例,并提倡物理学家通过特定网站贡献问题。

arXiv:2507.21695v1 Announce Type: cross Abstract: We introduce a benchmark framework developed by and for the scientific community to evaluate, monitor and steer large language model development in fundamental physics. Building on philosophical concepts of scientific understanding and creativity, we develop a scoring system in which each question is scored by an expert for its correctness, difficulty, and surprise. The questions are of three forms: (i) multiple-choice questions for conceptual understanding, (ii) analytical problems requiring mathematical derivation, and (iii) openended tasks requiring complex problem solving. Our current dataset contains diverse set of examples, including a machine learning challenge to classify high-energy physics events, such as the four top quark signal. To ensure continued relevance, we propose a living benchmark, where physicists contribute questions, for instance alongside new publications. We invite contributions via: http://www.physicsbenchmarks.org/. We hope that this benchmark will enable a targeted AI development that can make a meaningful contribution to fundamental physics research.

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AI评估框架 基础物理 科学理解
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