AI RESEARCH
VLMs are Good Teachers for Video Reasoning via Adaptive Test-Time Optimization
arXiv CS.CV
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ArXi:2606.02564v1 Announce Type: new The recent "Reasoning with Video" paradigm utilizes Video Generation Models (VGMs) to generate temporally coherent visual trajectories to complete reasoning tasks. Although state-of-the-art VGMs excel at visual quality, they often struggle to understand and follow task-specific rules, leading to logical failures across diverse reasoning scenarios. Existing efforts try to utilize Vision-Language Models (VLMs) as problem pre-solvers to produce or refine textual guidance for the.