7 papers · 1 filter
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…
EgoSteer: A Full-Stack System Towards Steerable Dexterous Manipulation from Egocentric Videos
Yifan Zhong, Zhang Chen, Tianrui Guan +13
Steerability is a defining capability of generalist robot policies, yet remains largely absent in dexterous-hand systems for lack of large-scale, language-aligned, and action-accur…
Long-Horizon Manipulation via Trace-Conditioned VLA Planning
Isabella Liu, An-Chieh Cheng, Rui Yan +7
Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to compounding execution errors.…
Human-Robot Copilot for Data-Efficient Imitation Learning
Rui Yan, Zaitian Gongye, Lars Paulsen +2
Collecting human demonstrations via teleoperation is a common approach for teaching robots task-specific skills. However, when only a limited number of demonstrations are available…
System Design for Maintaining Internal State Consistency in Long-Horizon Robotic Tabletop Games
Guangyu Zhao, Ceyao Zhang, Chengdong Ma +16
Long-horizon tabletop games pose a distinct systems challenge for robotics: small perceptual or execution errors can invalidate accumulated task state, propagate across decision-ma…
ACE-F: A Cross Embodiment Foldable System with Force Feedback for Dexterous Teleoperation
Rui Yan, Jiajian Fu, Shiqi Yang +3
Teleoperation systems are essential for efficiently collecting diverse and high-quality robot demonstration data, especially for complex, contact-rich tasks. However, current teleo…