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cs.CV2026
Imagine the Future, Internalize the Gist: Efficient VLA Reasoning via Internalized Spatiotemporal Imagination
Shenglan Li, Zhendong Mi, Hengyi Zhu +6
Vision-language-action (VLA) models increasingly incorporate intermediate reasoning to improve robotic manipulation, yet existing approaches primarily reason about observed states…
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…