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cs.CV2026
ACPruner: Visual Token Pruning as Biased Attention Coverage Maximization in LVLMs
Xu Li, Yuxuan Liang, Yi Zheng +6
Large Vision-Language Models (LVLMs) face significant computational inefficiencies caused by the large number of visual tokens. Existing visual token pruning methods mainly focus o…
cs.CV2026
CAR-VLA: Complexity-Aware and Risk-Adaptive Reasoning for Autonomous Driving
Xiaolei Chen, Zhuolin He, Yuxuan Liang +14
Existing adaptive reasoning methods for driving Vision-Language-Action (VLA) models primarily focus on whether to reason, overlooking how reasoning should differ across driving sit…