5 papers
SKIP: Sparse Keyframe Interpolation Paradigm for Efficient Embodied World Models
Ziheng He, Yixiang Chen, Ning Yang +11
Embodied world models have emerged as a promising paradigm in robotics by predicting how robot actions affect the surrounding scene. However, the rollout inference remains computat…
EgoKit: Towards Unified Low-Cost Egocentric Data Collection with Heterogeneous Devices
Liuchuan Yu, Erdem Murat, Beichen Wang +10
Egocentric video is increasingly used as a data source for robot learning, activity understanding, and embodied AI research, but collecting it at scale remains fragmented in practi…
XRoboToolkit: A Cross-Platform Framework for Robot Teleoperation
Zhigen Zhao, Liuchuan Yu, Ke Jing +1
The rapid advancement of Vision-Language-Action models has created an urgent need for large-scale, high-quality robot demonstration datasets. Although teleoperation is the predomin…
Fine-tuning Diffusion Policies with Backpropagation Through Diffusion Timesteps
Ningyuan Yang, Jiaxuan Gao, Feng Gao +2
Diffusion policies, widely adopted in decision-making scenarios such as robotics, gaming and autonomous driving, are capable of learning diverse skills from demonstration data due…
TW-CRL: Time-Weighted Contrastive Reward Learning for Efficient Inverse Reinforcement Learning
Yuxuan Li, Yicheng Gao, Ning Yang +1
Episodic tasks in Reinforcement Learning (RL) often pose challenges due to sparse reward signals and high-dimensional state spaces, which hinder efficient learning. Additionally, t…