5 papers
PhysBrain 1.0 Technical Report
Shijie Lian, Bin Yu, Xiaopeng Lin +10
Vision-language-action models have advanced rapidly, but robot trajectories alone provide limited coverage for learning broad physical understanding. PhysBrain 1.0 studies a comple…
STARRY: Spatial-Temporal Action-Centric World Modeling for Robotic Manipulation
Yuxuan Tian, Yurun Jin, Bin Yu +5
Robotic manipulation requires reasoning about future spatial-temporal interactions and geometric constraints, yet existing Vision-Language-Action (VLA) policies often leave predict…
VLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image Reasoning
Chaoyang Wang, Wenrui Bao, Sicheng Gao +5
Vision-Language-Action (VLA) models have shown promising capabilities for embodied intelligence, but most existing approaches rely on text-based chain-of-thought reasoning where vi…
RoboGrasp: A Universal Grasping Policy for Robust Robotic Control
Yiqi Huang, Travis Davies, Jiahuan Yan +3
Imitation learning and world models have shown significant promise in advancing generalizable robotic learning, with robotic grasping remaining a critical challenge for achieving p…
Spatially Visual Perception for End-to-End Robotic Learning
Travis Davies, Jiahuan Yan, Xiang Chen +4
Recent advances in imitation learning have shown significant promise for robotic control and embodied intelligence. However, achieving robust generalization across diverse mounted…