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cs.RO2026
ActFovea: Runtime Safeguarding for VLA Policies via Spatiotemporal Visual-Action Consistency
Wenda Yu, Tianshi Wang, Fengling Li +3
Vision-language-action (VLA) policies achieve strong performance in robotic manipulation but remain vulnerable to runtime disturbances that break the temporal alignment among visua…
cs.RO2026
DA-PTQ: Drift-Aware Post-Training Quantization for Efficient Vision-Language-Action Models
Siyuan Xu, Tianshi Wang, Fengling Li +2
Vision-Language-Action models (VLAs) have demonstrated strong potential for embodied AI, yet their deployment on resource-limited robots remains challenging due to high memory and…
cs.RO2026
AC^2-VLA: Action-Context-Aware Adaptive Computation in Vision-Language-Action Models for Efficient Robotic Manipulation
Wenda Yu, Tianshi Wang, Fengling Li +2
Vision-Language-Action (VLA) models have demonstrated strong performance in robotic manipulation, yet their closed-loop deployment is hindered by the high latency and compute cost…