AI RESEARCH
CIVIC: End-to-End Sequence Compactness for Efficient Vision-Language Models
arXiv CS.AI
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ArXi:2605.28115v1 Announce Type: new Vision-Language Models (VLMs) face severe memory and latency bottlenecks due to high-resolution visual tokens. While current token reduction methods theoretically save FLOPs, post-hoc pruning