World-Action Models inherit world knowledge from video-generative priors, and channel it into executable control signals through embodied experience. Existing systems, however, are monolithic: the generative backbone, visual representation, architecture, information flow, inference procedure, and training data are tigh...
Yu-Ran Wang, Siqiao Huang, Ming-Lei Li et al.· 38 citations· ⚡4
Rolling-WAM is presented, a formulation that distributes joint denoising across successive replanning cycles and delivers a 4.5x steady-state replanning speedup over standard joint WAMs.
Ying Zhou, Jun-Jie Ye, Yi-Qi Zhao et al.· 0 citations
Jetson-PI is proposed, a method for efficient VLA deployment on onboard devices via Foresight-Aligned Asynchronous Correction that trains a lightweight future correction module that predicts future environment representation conditioned on committed actions, enabling the action expert to directly predict actions from t...
Zebin Yang, Qi Wang, Yun-He Wang et al.· arXiv.org· 2 citations
Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard devices, such as the Jetson Orin, remains challenging due to their high computational complexity, which leads to substantial inference latency and low control frequency....
Zebin Yang, Qi Wang, Yun-He Wang et al.· 1 citation
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