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cs.CV2026
Who Speaks for the Pruned? Visual Token Pruning as Coverage Optimization
Qingchan Zhu, Weihang You, Hanqi Jiang +3
Visual token pruning reduces the inference cost of vision-language models (VLMs), but most methods only ask which tokens to keep. This retained-token view can keep redundant high-s…
cs.CV2026
ViThinker: Active Vision-Language Reasoning via Dynamic Perceptual Querying
Weihang You, Qingchan Zhu, David Liu +3
Chain-of-Thought (CoT) reasoning excels in language models but struggles in vision-language models due to premature visual-to-text conversion that discards continuous information s…