AI RESEARCH
LongVideo-R1: Smart Navigation for Low-cost Long Video Understanding
arXiv CS.CV
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ArXi:2602.20913v2 Announce Type: replace This paper addresses the critical and underexplored challenge of long video understanding with low computational budgets. We propose LongVideo-R1, an active, reasoning-equipped multimodal large language model (MLLM) agent designed for efficient video context navigation, avoiding the redundancy of exhaustive search. At the core of LongVideo-R1 lies a reasoning module that leverages high-level visual cues to infer the most informative video clip for subsequent processing.