activity
20242026
collaborators

10 papers

cs.RO2026

Factor-Aware Mixture-of-Experts with Pretrained Encoder for Combinatorial Generalization

Feihong Zhang, Guojian Zhan, Zeyu He +8

The integration of pretrained encoders with diffusion policies has become a dominant paradigm for visual robotic manipulation. However, it still struggles to generalize across comp…

cs.LG2026

Real-Time Generative Policy via Langevin-Guided Flow Matching for Autonomous Driving

Tianze Zhu, Yinuo Wang, Wenjun Zou +6

Reinforcement learning (RL) is a fundamental methodology in autonomous driving systems, where generative policies exhibit considerable potential by leveraging their ability to mode…

cs.RO2025

World In Your Hands: A Large-Scale and Open-Source Ecosystem for Learning Human-Centric Manipulation in the Wild

Yupeng Zheng, Jichao Peng, Weize Li +22

We introduce World In Your Hands (WIYH), a large-scale open-source ecosystem comprising over 1,000 hours of human manipulation data collected in-the-wild with millimeter-scale moti…

cs.LG2025

Bootstrap Off-policy with World Model

Guojian Zhan, Likun Wang, Xiangteng Zhang +3

Online planning has proven effective in reinforcement learning (RL) for improving sample efficiency and final performance. However, using planning for environment interaction inevi…

cs.AI2025

Off-policy Reinforcement Learning with Model-based Exploration Augmentation

Likun Wang, Xiangteng Zhang, Yinuo Wang +5

Exploration is fundamental to reinforcement learning (RL), as it determines how effectively an agent discovers and exploits the underlying structure of its environment to achieve o…

cs.LG2025

Mind Your Entropy: From Maximum Entropy to Trajectory Entropy-Constrained RL

Guojian Zhan, Likun Wang, Pengcheng Wang +4

Maximum entropy has become a mainstream off-policy reinforcement learning (RL) framework for balancing exploitation and exploration. However, two bottlenecks still limit further pe…

cs.LG2025

Distributional Soft Actor-Critic with Diffusion Policy

Tong Liu, Yinuo Wang, Xujie Song +6

Reinforcement learning has been proven to be highly effective in handling complex control tasks. Traditional methods typically use unimodal distributions, such as Gaussian distribu…

cs.LG2025

Enhanced DACER Algorithm with High Diffusion Efficiency

Yinuo Wang, Likun Wang, Mining Tan +11

Due to their expressive capacity, diffusion models have shown great promise in offline RL and imitation learning. Diffusion Actor-Critic with Entropy Regulator (DACER) extended thi…

eess.SY2024

Controllability Test for Nonlinear Datatic Systems

Yujie Yang, Letian Tao, Likun Wang +1

Controllability is a fundamental property of control systems, serving as the prerequisite for controller design. While controllability test is well established in modelic (i.e., mo…

cs.LG2024

Diffusion Actor-Critic with Entropy Regulator

Yinuo Wang, Likun Wang, Yuxuan Jiang +8

Reinforcement learning (RL) has proven highly effective in addressing complex decision-making and control tasks. However, in most traditional RL algorithms, the policy is typically…