Extent of Genuine Reasoning in Current Video Generation Models

Determine the extent to which contemporary video generation models such as Veo-3 genuinely exhibit reasoning about the content they create, as opposed to merely producing coherent sequences through surface-level pattern generation.

Background

The paper investigates whether recent text-to-video models exhibit emergent reasoning capabilities beyond high-fidelity synthesis. Although these models can maintain temporal coherence and realistic motion, prior evidence suggests they may rely on pattern replay rather than principled reasoning.

Motivated by this uncertainty, the authors introduce an empirical paper centered on Veo-3 and curate the MME-CoF benchmark to test Chain-of-Frame reasoning across spatial, geometric, physical, temporal, and embodied categories. The open question highlights the need to rigorously characterize genuine reasoning versus visually plausible generation.