3 papers
cs.AI2026
SeePhys Pro: Diagnosing Modality Transfer and Blind-Training Effects in Multimodal RLVR for Physics Reasoning
Kun Xiang, Terry Jingchen Zhang, Zirong Liu +15
We introduce SeePhys Pro, a fine-grained modality transfer benchmark that studies whether models preserve the same reasoning capability when critical information is progressively t…
cs.AI2026
Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI
Kun Xiang, Terry Jingchen Zhang, Yinya Huang +13
The rapid advancement of embodied intelligence and world models has intensified efforts to integrate physical laws into AI systems, yet physical perception and symbolic physics rea…
cs.AI2025
SeePhys: Does Seeing Help Thinking? -- Benchmarking Vision-Based Physics Reasoning
Kun Xiang, Heng Li, Terry Jingchen Zhang +11
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 fu…