2 citations · 4 across the 11 of their papers we have counts for
7 papers · 1 filter
Function beyond Form: Functional Correspondence for Cross-Embodiment Dexterous Grasp Generation
Bolin Zou, Wenlong Dong, Mu Ai +4
Cross-embodiment dexterous grasp generation remains challenging because robotic hands differ substantially in geometry, topology, and kinematics. Existing approaches often lack exp…
RoboICL: Embodied In-Context Learning with GPT-6 Astra
Fangcheng Liu, Yeqing Shen, Anda Cheng +7
General-purpose vision-language models offer a promising way to zero-shot robot control: \gptastra{} excels at open-ended and language- or image-conditioned manipulation but remain…
Imperfection for Precision: Upcycling Imperfect Data for High-Precision Robotic Manipulation
Hao Wei, Yang Liu, Chao Tang +7
Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation), which is slow and expensive…
What Matters in Designing World Action Models: An Empirical Study
Chao Tang, Haoqing Wang, Zilang Cen +9
World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing works often introduce unified s…
PSR: Predictive Sensorimotor Representation Learning for Contact-Rich Manipulation
Shengbao Li, Peng Xu, Chao Tang +8
Contact-rich manipulation requires policies to generate precise actions by reasoning over contact forces, robot configurations, and interaction histories beyond visual observations…
Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations
Chao Tang, Jiacheng Xu, Haofei Lu +4
Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vast diversity of objects and t…
Easy-IIL: Reducing Human Operational Burden in Interactive Imitation Learning via an Assistant Expert
Chengjie Zhang, Chao Tang, Wenlong Dong +3
Interactive Imitation Learning (IIL) typically relies on extensive human involvement for both offline demonstration and online interaction. Prior work primarily focuses on reducing…