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PHYRD: A Living Benchmark for Reproducing and Extending Theoretical Physics Research
Qituan Zhang, Guo Chen, Linfeng Zhang, Wenlong Zhang

PHYRD: A Living Benchmark for Reproducing and Extending Theoretical Physics Research

Computer Science & Mathematics Published 2026 Verification Pending

Overview & Synopsis

Large language models and agents have shown significant power in advanced physical research. In this paper, We introduce PHYRD, a living benchmark for theoretical-physics reasoning with 63 Reproduce and 43 Discover problems. Reproduce tests derivation of published results; Discover tests consequences of modified theoretical conditions. FormulaForest constructs the tasks with reference solutions and subquestion-level rubrics. Across five models, whole-problem accuracy ranges from 49.21% to 68.25% on Reproduce and from 18.60% to 74.42% on closed-book Discover. With tools, four models complete more Discover problems, but conceptual errors and missing arguments persist. Besides, our experimental results demonstrate the value of FormulaForest as synthetic data. On FrontierScience, a benchmark developed by OpenAI, it raises the accuracy of a Qwen-35B-A3B model from 61% to 72%.

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Indexed from repository: arXiv (arxiv.org)
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Document Information

Document Title PHYRD: A Living Benchmark for Reproducing and Extending Theoretical Physics Research
Author / Organization Qituan Zhang, Guo Chen, Linfeng Zhang, Wenlong Zhang
Subject & Discipline cs.CL
Categories Computer Science & Mathematics
Publication Year 2026
License / Rights arXiv Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website arXiv (arxiv.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-118544
Original Source Link Visit Source Page on arxiv.org »