Summary
This paper investigates the reasoning capabilities of diffusion-based video models, challenging the prior assumption that reasoning occurs sequentially across video frames (Chain-of-Frames). Instead, the research reveals that reasoning primarily emerges along the diffusion denoising steps. This finding offers a new understanding of the underlying mechanisms by which these models process and infer information.
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