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cs.CV2026
GRIP-VLM: Group-Relative Importance Pruning for Efficient Vision-Language Models
Mingzhe Huang, Weijun Wang, Xin Ding +7
In Vision-Language Models (VLMs), processing a massive number of visual tokens incurs prohibitive computational overhead. While recent training-aware pruning methods attempt to sel…
cs.CV2026
Em-Garde: A Propose-Match Framework for Proactive Streaming Video Understanding
Yikai Zheng, Xin Ding, Yifan Yang +6
Recent advances in Streaming Video Understanding has enabled a new interaction paradigm where models respond proactively to user queries. Current proactive VideoLLMs rely on per-fr…
cs.CV2026
ROCKET: Residual-Oriented Multi-Layer Alignment for Spatially-Aware Vision-Language-Action Models
Guoheng Sun, Tingting Du, Kaixi Feng +6
Vision-Language-Action (VLA) models enable instruction-following robotic manipulation, but they are typically pretrained on 2D data and lack 3D spatial understanding. An effective…