3 papers
cs.CV2026
Q-Zoom: Query-Aware Adaptive Perception for Efficient Multimodal Large Language Models
Yuheng Shi, Xiaohuan Pei, Linfeng Wen +2
MLLMs require high-resolution visual inputs for fine-grained tasks like document understanding and dense scene perception. However, current global resolution scaling paradigms indi…
cs.CV2026
Catching the Details: Self-Distilled RoI Predictors for Fine-Grained MLLM Perception
Yuheng Shi, Xiaohuan Pei, Minjing Dong +1
Multimodal Large Language Models (MLLMs) require high-resolution visual information to perform fine-grained perception, yet processing entire high-resolution images is computationa…
cs.RO2025
Action-aware Dynamic Pruning for Efficient Vision-Language-Action Manipulation
Xiaohuan Pei, Yuxing Chen, Siyu Xu +3
Robotic manipulation with Vision-Language-Action models requires efficient inference over long-horizon multi-modal context, where attention to dense visual tokens dominates computa…