5 papers · 1 filter
X-WBC: A Cross-Embodiment Foundation Model for Humanoid Whole-Body Control
Juntong Zhang, Chun Gu, Li Zhang
Scaling humanoid whole-body control toward general-purpose deployment requires large human motion corpora and training experience shared across robot bodies. Existing methods usual…
Learning Transferable Dynamics Priors from Action to World Modeling
Ze Huang, Jiahui Zhang, Hairuo Liu +3
We study action-conditioned world modeling as a scalable way to learn transferable dynamics priors for robot learning. By pretraining a model to predict how actions drive visual sc…
ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning
Wei Xiao, Weiliang Tang, Yuying Ge +4
Human interventions provide crucial corrective signals for post-training Vision-Language-Action (VLA) models. However, enabling seamless humanoid interventions is a formidable syst…
RoboRouter: Training-Free Policy Routing for Robotic Manipulation
Yiteng Chen, Zhe Cao, Hongjia Ren +9
Research on robotic manipulation has developed a diverse set of policy paradigms, including vision-language-action (VLA) models, vision-action (VA) policies, and code-based composi…
Reinforcing Action Policies by Prophesying
Jiahui Zhang, Ze Huang, Chun Gu +2
Vision-Language-Action (VLA) policies excel in aligning language, perception, and robot control. However, most VLAs are trained purely by imitation, which overfits to demonstration…