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cs.RO2026
StateMem: Single-State Residual Memory with Adaptive Inference for Vision-Language-Action Policies
Wenzhuo Li, Qiongfeng Shi, Yi Zhou
Memory-dependent robotic manipulation often requires later actions to use information from earlier interactions. Existing vision-language-action (VLA) policies primarily rely on cu…
cs.RO2026
OrthoSkillVLA: Continual Skill Learning via Gradient-Informed Skill Subspace Adaptation
Jiaqi Wang, Zhou Fang, Qiongfeng Shi +1
Pretrained Vision-Language-Action models provide a strong foundation for robot learning, but sequentially adapting them to diverse skills can perturb the representations and veloci…
cs.RO2026
ProbeFlow: Training-Free Adaptive Flow Matching for Vision-Language-Action Models
Zhou Fang, Jiaqi Wang, Yi Zhou +2
Vision-Language-Action (VLA) policies increasingly use Flow Matching (FM) action heads to generate action chunks as continuous trajectories. At inference, an FM head solves an ordi…