5 citations · 5 across the 6 of their papers we have counts for
6 papers
PLAT: Sparse Timed Keyframe Motion Tracking for Humanoid Control via Privileged Latent Transition Learning
Zepeng Wang, Jiangxing Wang, Chao Ma +2
Humanoid motion tracking policies rely on dense frame-by-frame references, limiting their use as high-level motion controllers for planning and interactive motion generation. We st…
General Humanoid Whole-Body Control via Pretraining and Fast Adaptation
Zepeng Wang, Jiangxing Wang, Shiqing Yao +8
Learning a general whole-body controller for humanoid robots remains challenging due to the diversity of motion distributions, the difficulty of fast adaptation, and the need for r…
RL from Physical Feedback: Aligning Large Motion Models with Humanoid Control
Junpeng Yue, Zepeng Wang, Yuxuan Wang +7
This paper focuses on a critical challenge in robotics: translating text-driven human motions into executable actions for humanoid robots, enabling efficient and cost-effective lea…
CORD: Generalizable Cooperation via Role Diversity
Kanefumi Matsuyama, Kefan Su, Jiangxing Wang +2
Cooperative multi-agent reinforcement learning (MARL) aims to develop agents that can collaborate effectively. However, most cooperative MARL methods overfit training agents, makin…
NOLO: Navigate Only Look Once
Bohan Zhou, Zhongbin Zhang, Jiangxing Wang +1
The in-context learning ability of Transformer models has brought new possibilities to visual navigation. In this paper, we focus on the video navigation setting, where an in-conte…
More Centralized Training, Still Decentralized Execution: Multi-Agent Conditional Policy Factorization
Jiangxing Wang, Deheng Ye, Zongqing Lu
In cooperative multi-agent reinforcement learning (MARL), combining value decomposition with actor-critic enables agents to learn stochastic policies, which are more suitable for t…