19 citations · 31 across the 6 of their papers we have counts for
4 papers · 1 filter
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
Chi-Lam Cheang, Guangzeng Chen, Ya Jing +9
We present GR-2, a state-of-the-art generalist robot agent for versatile and generalizable robot manipulation. GR-2 is first pre-trained on a vast number of Internet videos to capt…
Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation
Hongtao Wu, Ya Jing, Chilam Cheang +6
Generative pre-trained models have demonstrated remarkable effectiveness in language and vision domains by learning useful representations. In this paper, we extend the scope of th…
Vision-Language Foundation Models as Effective Robot Imitators
Xinghang Li, Minghuan Liu, Hanbo Zhang +9
Recent progress in vision language foundation models has shown their ability to understand multimodal data and resolve complicated vision language tasks, including robotics manipul…