5 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…
AdaptGrad: Adaptive Sampling to Reduce Noise
Linjiang Zhou, Chao Ma, Zepeng Wang +2
Gradient Smoothing is an efficient approach to reducing noise in gradient-based model explanation method. SmoothGrad adds Gaussian noise to mitigate much of these noise. However, t…
: Towards Effective and Efficient Cost Function Design for Safe Reinforcement Learning via Large Language Model
Zepeng Wang, Chao Ma, Linjiang Zhou +4
Different classes of safe reinforcement learning algorithms have shown satisfactory performance in various types of safety requirement scenarios. However, the existing methods main…
Axiomatization of Gradient Smoothing in Neural Networks
Linjiang Zhou, Xiaochuan Shi, Chao Ma +1
Gradients play a pivotal role in neural networks explanation. The inherent high dimensionality and structural complexity of neural networks result in the original gradients contain…