World-Action Models (WAMs) couple visual dynamics with action prediction, bringing the rich priors of pretrained video models to robotic manipulation. However, their multi-view interfaces typically tile images or concatenate tokens, leaving the geometric relationships among synchronized cameras implicit. This makes it...
Wen-Bo Chen, Tian-Fu Li, Hao-Xuan Xu et al.· 0 citations
Vision-Language-Action models are increasingly effective for robotic manipulation, yet most predict actions directly from current observations without explicitly modeling future scene evolution. Recent methods introduce future prediction to improve action generation, but dense future modeling often requires expensive i...
Tian-Fu Li, Hao-Xuan Xu, Wen-Bo Chen et al.· 0 citations
Safe and efficient trajectory planning is essential in autonomous driving. However, existing end-to-end approaches often fall short in both computational efficiency and safety guarantees. Methods based on imitation learning suffer from causal confusion, while rule-based scoring approaches often incur heavy computationa...
Cheng-Lin Chen, Lu-Jia Wang, Xin-Hu Zheng et al.· 0 citations
DreamTrajectory is presented, a trajectory-guided framework for language-conditioned mobile manipulation that introduces one component for each limitation of existing Vision-Language-Action policies, and jointly predicts an intention-level end-effector trajectory and a whole-body action chunk in a single action expert.
Zheng Yang, Wen-Jie Zhang, Xiang-Yu Chen et al.· 1 citation
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