10 citations · 15 across the 6 of their papers we have counts for
7 papers
A Practical Recipe Towards Improving Sim-and-Real Correlation for VLA Evaluation
Shuo Wang, Hanyuan Xu, Yingdong Hu +2
Simulation has become an essential tool for evaluating and improving vision-language-action (VLA) policies, offering scalable, reproducible, and controllable alternatives to costly…
A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation
Fanqi Lin, Kushal Arora, Jean Mercat +9
Large behavior models have shown strong dexterous manipulation capabilities by extending imitation learning to large-scale training on multi-task robot data, yet their generalizati…
OneTwoVLA: A Unified Vision-Language-Action Model with Adaptive Reasoning
Fanqi Lin, Ruiqian Nai, Yingdong Hu +3
General-purpose robots capable of performing diverse tasks require synergistic reasoning and acting capabilities. However, recent dual-system approaches, which separate high-level…
HuB: Learning Extreme Humanoid Balance
Tong Zhang, Boyuan Zheng, Ruiqian Nai +8
The human body demonstrates exceptional motor capabilities-such as standing steadily on one foot or performing a high kick with the leg raised over 1.5 meters-both requiring precis…
Data Scaling Laws in Imitation Learning for Robotic Manipulation
Fanqi Lin, Yingdong Hu, Pingyue Sheng +3
Data scaling has revolutionized fields like natural language processing and computer vision, providing models with remarkable generalization capabilities. In this paper, we investi…
CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models
Haoxu Huang, Fanqi Lin, Yingdong Hu +2
Foundation models pre-trained on web-scale data are shown to encapsulate extensive world knowledge beneficial for robotic manipulation in the form of task planning. However, the ac…
Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning
Yingdong Hu, Fanqi Lin, Tong Zhang +2
In this study, we are interested in imbuing robots with the capability of physically-grounded task planning. Recent advancements have shown that large language models (LLMs) posses…