AI RESEARCH
Video Models Can Reason with Verifiable Rewards
arXiv CS.CV
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ArXi:2605.15458v1 Announce Type: new Video diffusion models have made rapid progress in perceptual realism and temporal coherence, but they remain primarily optimized for plausible generation rather than verifiable reasoning. This limitation is especially pronounced in tasks where generated videos must satisfy explicit spatial, temporal, or logical constraints. Inspired by the role of reinforcement learning with verifiable rewards (RLVR) in reasoning-oriented language models, we