IEEE

Bimanual Long-Horizon Manipulation Via Temporal-Context Transformer RL

Abstract: Dual-arm robots can perform bimanual long-horizon (LH) manipulation, surpassing the capabilities of single-arm robots. However, bimanual LH tasks are challenging for robot intelligence due ...
GitHub

Demystifying Reinforcement Learning in Agentic Reasoning

An overview of our research on agentic RL. In this work, we systematically investigate three dimensions of agentic RL: data, algorithms, and reasoning modes. Our findings reveal: Real end-to-end ...
GitHub

Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models

We propose TraceRL, a trajectory-aware reinforcement learning method for diffusion language models, which demonstrates the best performance among RL approaches for DLMs. We also introduce a ...
IEEE

A Hybrid Framework Using Diffusion Policy and Residual RL for Force-Sensitive Robotic Manipulation

Abstract: Force-sensitive manipulation is essential for tasks such as cleaning, polishing, and surgical assistance, yet it remains challenging due to complex contact dynamics and the need for ...