7 citations · 9 across the 9 of their papers we have counts for
10 papers
Translation as a Bridging Action: Transferring Manipulation Skills from Humans to Robots
Sijin Chen, Kaixuan Jiang, Haixin Shi +6
We study whether we can learn novel manipulation skills from human actions to a bi-manual robot with parallel grippers. Human action data is cheap, abundant, and diverse, making it…
Towards Generalizable Robotic Data Flywheel: High-Dimensional Factorization and Composition
Yuyang Xiao, Yifei Zhou, Haoran Wang +2
The lack of sufficiently diverse data, coupled with limited data efficiency, remains a major bottleneck for generalist robotic models, yet systematic strategies for collecting and…
World Guidance: World Modeling in Condition Space for Action Generation
Yue Su, Sijin Chen, Haixin Shi +7
Leveraging future observation modeling to facilitate action generation presents a promising avenue for enhancing the capabilities of Vision-Language-Action (VLA) models. However, e…
GR-Dexter Technical Report
Ruoshi Wen, Guangzeng Chen, Zhongren Cui +23
Vision-language-action (VLA) models have enabled language-conditioned, long-horizon robot manipulation, but most existing systems are limited to grippers. Scaling VLA policies to b…
GR-RL: Going Dexterous and Precise for Long-Horizon Robotic Manipulation
Yunfei Li, Xiao Ma, Jiafeng Xu +18
We present GR-RL, a robotic learning framework that turns a generalist vision-language-action (VLA) policy into a highly capable specialist for long-horizon dexterous manipulation.…
From Spatial to Actions: Grounding Vision-Language-Action Model in Spatial Foundation Priors
Zhengshen Zhang, Hao Li, Yalun Dai +10
Existing vision-language-action (VLA) models act in 3D real-world but are typically built on 2D encoders, leaving a spatial reasoning gap that limits generalization and adaptabilit…
GR-3 Technical Report
Chilam Cheang, Sijin Chen, Zhongren Cui +18
We report our recent progress towards building generalist robot policies, the development of GR-3. GR-3 is a large-scale vision-language-action (VLA) model. It showcases exceptiona…
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…
IRASim: A Fine-Grained World Model for Robot Manipulation
Fangqi Zhu, Hongtao Wu, Song Guo +3
World models allow autonomous agents to plan and explore by predicting the visual outcomes of different actions. However, for robot manipulation, it is challenging to accurately mo…