Grounding Video Reasoning in Physical Signals
Physical video understanding requires more than naming an event correctly. A model can answer a question about pouring, sliding, or collision from textual regularities while still failing to localize the event in time or space. We introduce a grounded benchmark for physical video understanding that extends the what--when--where evaluation structure of V-STaR to four video sources, six physics domains, three prompt families (physics, vstar_like, and neutral_rstr), and four input conditions (original, shuffled, ablated, and frame-masked). The benchmark contains 1,560 base video clips from SSV2, YouCook2, HoloAssist, and Roundabout-TAU. Each clip is first converted into a shared grounded eve...
| Authors | Alibay Osmanli, Zixu Cheng, Shaogang Gong |
|---|---|
| Primary category | cs.CV |
| Published | 23 April 2026 |
| Last updated at source | 23 April 2026 |
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