4 papers · 1 filter
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…
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…
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…
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…