2 papers
cs.RO2026
WorldSample: Closed-loop Real-robot RL with World Modelling
Yuquan Xue, Le Xu, Zeyi Liu +5
Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-and-error interaction beyond t…
cs.RO2026
RESample: A Robust Data Augmentation Framework via Exploratory Sampling for Robotic Manipulation
Yuquan Xue, Guanxing Lu, Zhenyu Wu +4
Vision-Language-Action (VLA) models have shown strong manipulation capability when trained with large-scale imitation learning datasets. However, these datasets that predominantly…