AI RESEARCH
Em-Garde: A Propose-Match Framework for Proactive Streaming Video Understanding
arXiv CS.AI
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ArXi:2603.19054v1 Announce Type: cross Recent advances in Streaming Video Understanding has enabled a new interaction paradigm where models respond proactively to user queries. Current proactive VideoLLMs rely on per-frame triggering decision making, which suffers from an efficiency-accuracy dilemma. We propose Em-Garde, a novel framework that decouples semantic understanding from streaming perception.