3 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
REDIRECT: A 1% Fix for Bad Robot Habits
Yu Zhang, Jiazhuo Li, Yancong Wei +3
Robots can acquire bad habits from a few defective moments in otherwise useful teleoperation. In mixed-quality robot data, normal and problematic demonstrations share most task beh…
TraceFlow: Guiding Frozen Flow-Matching Robot Policies with Success and Failure Traces
Jiaxuan Zhang, Ruizhe Liu, Yu Zhang +1
A vision-language-action (VLA) policy with a flow-matching action expert generates each action chunk (a short command sequence) by integrating a learned velocity field; once its we…
The Imitator Game: Benchmarking Robot Imitative Ability Beyond Action Prediction
Xunzhe Zhou, Yiyang Cai, Fengyi Wang +9
Humans imitate at the level of intent: given a demonstration, we infer its goal and carry it out with whatever tools, objects, and layouts are at hand. Current robot policies inste…
Rethinking Demonstration Unlearning in Imitation Learning for Robotics
Jiazhuo Li, Yu Zhang, Yiming Fei +4
Imitation learning for robotics depends on human demonstrations, some of which people may later ask to remove. Retraining without them is the natural reference, but its cost grows…
D-SPEAR: Dual-Stream Prioritized Experience Adaptive Replay for Stable Reinforcement Learning in Robotic Manipulation
Yu Zhang, Karl Mason
Robotic manipulation remains challenging for reinforcement learning due to contact-rich dynamics, long horizons, and training instability. Although off-policy actor-critic algorith…