arXiv Computer Vision August 21, 2026 By Yanxiang Huang, Guohua Gao, Zhaoyang Wei

Video Evidence to Reasoning Efficient Video Understanding via Explicit Evidence Grounding

Read the original on arXiv Computer Vision →

arXiv:2601. 07761v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) face a fundamental dilemma in video reasoning: they are caught between the prohibitive computational costs of verbose reasoning and the hallucination risks of efficient, ungrounded approaches.

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