6 citations · 13 across the 16 of their papers we have counts for
16 papers
BICPO-VLA: Behavior-Identified Continuation Preference Optimization for Smooth Asynchronous Vision-Language-Action Control
Ming Shang, Yuchen Huang, Jiaoyang Chen +8
The request-to-handoff gap has three coupled sources: ambiguity about the behavior intended at request time, physical-state drift accumulated during action generation, and residual…
PBD-AG: Persistent Baseline-Delta Active Graphs with Uncertainty-Aware Inspection for Long-Horizon Service Robots
Shuo Bao, Wei Dong, Shuyue Zhang +8
Long-horizon service robots require persistent world models that can be built autonomously in unseen environments and revised as task-relevant objects change. Existing methods rely…
Ratio-Variance Regularized Policy Optimization
Yu Luo, Shuo Han, Yihan Hu +5
Standard on-policy reinforcement learning relies on heuristic clipping to enforce trust regions, but this mechanism imposes a severe cost by indiscriminately truncating high-return…
FLAC: Maximum Entropy RL via Kinetic Energy Regularized Bridge Matching
Lei Lv, Yunfei Li, Yu Luo +2
Iterative generative policies, such as diffusion models and flow matching, offer superior expressivity for continuous control but complicate Maximum Entropy Reinforcement Learning…
Flow-Based Policy for Online Reinforcement Learning
Lei Lv, Yunfei Li, Yu Luo +4
We present \textbf{FlowRL}, a novel framework for online reinforcement learning that integrates flow-based policy representation with Wasserstein-2-regularized optimization. We arg…
Multi-segment Soft Robot Control via Deep Koopman-based Model Predictive Control
Lei Lv, Lei Liu, Lei Bao +7
Soft robots, compared to regular rigid robots, as their multiple segments with soft materials bring flexibility and compliance, have the advantages of safe interaction and dexterou…
Medical Multimodal Foundation Models in Clinical Diagnosis and Treatment: Applications, Challenges, and Future Directions
Kai Sun, Siyan Xue, Fuchun Sun +12
Recent advancements in deep learning have significantly revolutionized the field of clinical diagnosis and treatment, offering novel approaches to improve diagnostic precision and…
RoboGolf: Mastering Real-World Minigolf with a Reflective Multi-Modality Vision-Language Model
Hantao Zhou, Tianying Ji, Lukas Sommerhalder +5
Minigolf is an exemplary real-world game for examining embodied intelligence, requiring challenging spatial and kinodynamic understanding to putt the ball. Additionally, reflective…
Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments
Runfa Chen, Ling Wang, Yu Du +4
Learning policies for multi-entity systems in 3D environments is far more complicated against single-entity scenarios, due to the exponential expansion of the global state space as…
Bidirectional-Reachable Hierarchical Reinforcement Learning with Mutually Responsive Policies
Yu Luo, Fuchun Sun, Tianying Ji +1
Hierarchical reinforcement learning (HRL) addresses complex long-horizon tasks by skillfully decomposing them into subgoals. Therefore, the effectiveness of HRL is greatly influenc…
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts
Yu Luo, Tianying Ji, Fuchun Sun +3
Training reinforcement learning policies using environment interaction data collected from varying policies or dynamics presents a fundamental challenge. Existing works often overl…
Offline-Boosted Actor-Critic: Adaptively Blending Optimal Historical Behaviors in Deep Off-Policy RL
Yu Luo, Tianying Ji, Fuchun Sun +3
Off-policy reinforcement learning (RL) has achieved notable success in tackling many complex real-world tasks, by leveraging previously collected data for policy learning. However,…
Equivariant Local Reference Frames for Unsupervised Non-rigid Point Cloud Shape Correspondence
Ling Wang, Runfa Chen, Yikai Wang +6
Unsupervised non-rigid point cloud shape correspondence underpins a multitude of 3D vision tasks, yet itself is non-trivial given the exponential complexity stemming from inter-poi…
Smooth Computation without Input Delay: Robust Tube-Based Model Predictive Control for Robot Manipulator Planning
Yu Luo, Qie Sima, Tianying Ji +3
Model Predictive Control (MPC) has exhibited remarkable capabilities in optimizing objectives and meeting constraints. However, the substantial computational burden associated with…
ACE : Off-Policy Actor-Critic with Causality-Aware Entropy Regularization
Tianying Ji, Yongyuan Liang, Yan Zeng +7
The varying significance of distinct primitive behaviors during the policy learning process has been overlooked by prior model-free RL algorithms. Leveraging this insight, we explo…
RobotGPT: Robot Manipulation Learning from ChatGPT
Yixiang Jin, Dingzhe Li, Yong A +5
We present RobotGPT, an innovative decision framework for robotic manipulation that prioritizes stability and safety. The execution code generated by ChatGPT cannot guarantee the s…