Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation, yet complex contact-rich tasks often benefit from multi-camera observations that jointly capture the end effector, objects, and targets under occlusion. Existing multi-camera VLAs usually concatenate view tokens, leaving actio...
Jia-Rui Yang, Ye-Hao Lu, Yu-Ning Su et al.· 1 citation
Zero-shot cross-task generalization, where a policy must execute manipulation tasks never seen during training, remains a central challenge in robot learning. In large language models, a novel task can be performed simply by specifying it in the context, without any parameter update. This form of in-context learning (I...
Jia-Min Zhou, Qihang Zhang, Gangwei Xu et al.· 1 citation
TemporalFlow-VLA provides a compact, physically grounded interface for exploiting ordered execution history without explicit motion estimation or geometric processing at deployment, and shows its clearest advantage over prior methods on longer-horizon, multi-stage manipulation.
Jia-Rui Yang, Ye-Hao Lu, Yu-Ning Su et al.· 1 citation
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