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CoFiE: Coarse-to-Fine Evidence Selection for Efficient Streaming Video Understanding
Streaming video understanding requires Vision Language Models (VLLMs) to process growing video streams and answer user questions under tight latency constraints. Existing methods improve efficiency through token pruning and memory-bank schemes, but mainly reduce visual tokens after visual encoding.
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