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This work introduces a frame-selection method designed specifically for multiple-choice questions, and is the first to directly utilize answer choices as inference-time cues for selecting frames relevant to answering a question.
Multimodal large language models (MLLMs) cannot process every frame of a long video because of limitations in visual-token and computational budgets. Three primary approaches have been proposed to enhance their long-video understanding capabilities: (i) Retraining an MLLM on a large video corpus and/or extending its in...
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