4 papers
FACT: Failure-Aware Causal Training for World-Action Models
Quanquan Peng, Yutong Liang, Rui Yan +2
Recent world-action models (WAMs) show that co-training policies with future prediction can provide physical priors for action generation. Building on the future-prediction ability…
ConTrack: Constrained Hand Motion Tracking with Adaptive Trade-off Control
Yutong Liang, Quanquan Peng, Ri-Zhao Qiu +1
Human demonstrations provide strong priors for robot manipulation, yet it is non-trivial to transfer them to execute on real robots due to the kinematic gap. In dexterous manipulat…
Embodiment-Aware Generalist Specialist Distillation for Unified Humanoid Whole-Body Control
Quanquan Peng, Yunfeng Lin, Yufei Xue +2
Humanoid Whole-Body Controllers trained with reinforcement learning (RL) have recently achieved remarkable performance, yet many target a single robot embodiment. Variations in dyn…
Parental Guidance: Efficient Lifelong Learning through Evolutionary Distillation
Octi Zhang, Quanquan Peng, Rosario Scalise +1
Developing robotic agents that can perform well in diverse environments while showing a variety of behaviors is a key challenge in AI and robotics. Traditional reinforcement learni…