Kaiyue Feng
2025
Physics: Benchmarking Foundation Models on University-Level Physics Problem Solving
Kaiyue Feng
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Yilun Zhao
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Yixin Liu
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Tianyu Yang
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Chen Zhao
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John Sous
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Arman Cohan
Findings of the Association for Computational Linguistics: ACL 2025
We introduce Physics, a comprehensive benchmark for university-level physics problem solving. It contains 1,297 expert-annotated problems covering six core areas: classical mechanics, quantum mechanics, thermodynamics and statistical mechanics, electromagnetism, atomic physics, and optics.Each problem requires advanced physics knowledge and mathematical reasoning.We develop a robust automated evaluation system for precise and reliable validation. Our evaluation of leading foundation models reveals substantial limitations. Even the most advanced model, o3-mini, achieves only 59.9% accuracy, highlighting significant challenges in solving high-level scientific problems.Through comprehensive error analysis, exploration of diverse prompting strategies, and Retrieval-Augmented Generation (RAG)-based knowledge augmentation, we identify key areas for improvement, laying the foundation for future advancements.
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- Arman Cohan 1
- Yixin Liu 1
- John Sous 1
- Tianyu Yang 1
- Yilun Zhao 1
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