MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs
arXiv:2508.21044v2 Announce Type: replace Abstract: Video Large Language Models (VLLMs) excel in video understanding, but their excessive visual tokens pose a significant computational challenge for r