AI RESEARCH
EMCompress: Video-LLMs with Endomorphic Multimodal Compression
arXiv CS.CV
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ArXi:2508.21094v3 Announce Type: replace Video-LLMs face a fundamental tension in long-video reasoning: static, sparse frame sampling either dilutes evidence across task-irrelevant segments at significant cost or misses fine-grained temporal semantics altogether.