most citedEfficient Language-instructed Skill Acquisition via Reward-Policy Co-Evolution

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Revisiting Cross-Architecture Distillation: Adaptive Dual-Teacher Transfer for Lightweight Video Models

Ying Peng, Hongsen Ye, Changxin Huang +3

Vision Transformers (ViTs) have achieved strong performance in video action recognition, but their high computational cost limits their practicality. Lightweight CNNs are more effi…

cs.RO2025

Whole-Body Coordination for Dynamic Object Grasping with Legged Manipulators

Qiwei Liang, Boyang Cai, Rongyi He +5

Quadrupedal robots with manipulators offer strong mobility and adaptability for grasping in unstructured, dynamic environments through coordinated whole-body control. However, exis…

cs.RO2025

Automated Hybrid Reward Scheduling via Large Language Models for Robotic Skill Learning

Changxin Huang, Junyang Liang, Yanbin Chang +2

Enabling a high-degree-of-freedom robot to learn specific skills is a challenging task due to the complexity of robotic dynamics. Reinforcement learning (RL) has emerged as a promi…

cs.RO20241 cited

Efficient Language-instructed Skill Acquisition via Reward-Policy Co-Evolution

Changxin Huang, Yanbin Chang, Junfan Lin +3

The ability to autonomously explore and resolve tasks with minimal human guidance is crucial for the self-development of embodied intelligence. Although reinforcement learning meth…

cs.RO2024

Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning

Runhao Zeng, Dingjie Zhou, Qiwei Liang +6

Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large languag…