SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning
On the map: LLM reasoning → Spatial and embodied reasoning
Abstract (arXiv)
We present SeePhys, a large-scale multimodal benchmark for LLM reasoning grounded in physics questions ranging from middle school to PhD qualifying exams. The benchmark covers 7 fundamental domains spanning the physics discipline, incorporating 21 categories of highly heterogeneous diagrams. In contrast to prior works where visual elements mainly serve auxiliary purposes, our benchmark features a substantial proportion of vision-essential problems (75%) that mandate visual information extraction for correct solutions. Through extensive evaluation, we observe that even the most advanced visual reasoning models (e.g., Gemini-2.5-pro and o4-mini) achieve sub-60% accuracy on our benchmark. These results reveal fundamental challenges in current large language models' visual understanding capabilities, particularly in: (i) establishing rigorous coupling between diagram interpretation and physics reasoning, and (ii) overcoming their persistent reliance on textual cues as cognitive shortcuts.
Key facts. Cited by 34 papers in the map (data through 14 Oct 2026). Placed in Spatial and embodied reasoning, one of 17 directions in LLM reasoning. Builds on 33 of its 41 references that are in the map. First posted on arXiv 25 May 2025.
Builds on
33 of 41 references.
Closest ancestors · 5
Same direction, newest first
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- 2025UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models1 Feb
- 2022UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression6 Dec
Other references · 28
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- 2025Physics: Benchmarking Foundation Models on University-Level Physics Problem Solvingcited by 31
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Citing papers per year: 2025: 12; 2026: 22.
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