5 papers
Beyond Monotonic Progress: Retry-Supervised Value Learning for Robot Imitation
Xinyao Qin, Junjie Lu, Kaixin Wang +7
Human demonstrations for robot imitation learning often contain mistakes and corrective behaviors, such as imprecise grasps, object misalignment, unstable contact, and repeated att…
Reinforcing VLAs in Task-Agnostic World Models
Yucen Wang, Rui Yu, Fengming Zhang +5
Post-training Vision-Language-Action (VLA) models via reinforcement learning (RL) in learned world models has emerged as an effective strategy to adapt to new tasks without costly…
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts
Yuhua Jiang, Junjie Lu, Xinyao Qin +4
Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic control remains challenging. Full f…
UniSteer: Unified Noise Steering for Efficient Human-Guided VLA Adaptation
Junjie Lu, Xinyao Qin, Yuhua Jiang +6
Diffusion-based vision-language-action (VLA) models have emerged as strong priors for robotic manipulation, yet adapting them to real-world distributions remains challenging. In pa…
Integrating Diffusion-based Multi-task Learning with Online Reinforcement Learning for Robust Quadruped Robot Control
Xinyao Qin, Xiaoteng Ma, Yang Qi +6
Recent research has highlighted the powerful capabilities of imitation learning in robotics. Leveraging generative models, particularly diffusion models, these approaches offer not…