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How Far Are LLMs from Solving Olympiad-Level Physics Problems?

Paper Dataset NeurIPS 2026 License: MIT

News

  • 🎉 PhysElite has been accepted to NeurIPS 2026 ED track!

Overview

PhysElite is a bilingual, multimodal benchmark for evaluating Olympiad-level physics reasoning in large language models. It includes 10K+ problems, with visual diagrams, Chinese-English solution derivations, and final answers.

The paper evaluates 18 open-source and closed-source multimodal large language models. The strongest evaluated model achieves 33.7% answer accuracy, highlighting the challenge of advanced physics reasoning. Step-level evaluation further examines where models make mistakes during their solutions.

Citation

If you use PhysElite in your research, please cite:

@misc{xu2026physelite,
  title         = {PhysElite: How Far Are LLMs from Solving Olympiad-Level Physics Problems?},
  author        = {Ruoran Xu and Wending Gao and Liyunfeng Chen and Aixin Shi and Haoyu Cheng and Zixiang Fang and Yiqiang Zou and Qiufeng Wang},
  year          = {2026},
  eprint        = {2608.25097},
  archivePrefix = {arXiv},
  primaryClass  = {cs.AI},
  url           = {https://arxiv.org/abs/2608.25097}
}

About

[NeurIPS 2026] PhysElite: How Far Are LLMs from Solving Olympiad-Level Physics Problems?

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