5 citations · 6 across the 4 of their papers we have counts for
5 papers · 1 filter
Continue or Replan? Bernoulli-Continuation Policy Learning for Adaptive Horizon Execution
Weichen Xu, Zhenhua Liu, Lin Luo +8
Existing chunk-based Vision-Language-Action (VLA) models execute a fixed number of actions (i.e., execution horizon) before replanning, turning replanning into a task-agnostic peri…
VideoVLA: Video Generators Can Be Generalizable Robot Manipulators
Yichao Shen, Fangyun Wei, Zhiying Du +5
Generalization in robot manipulation is essential for deploying robots in open-world environments and advancing toward artificial general intelligence. While recent Vision-Language…
Scalable Vision-Language-Action Model Pretraining for Robotic Manipulation with Real-Life Human Activity Videos
Qixiu Li, Yu Deng, Yaobo Liang +14
This paper presents a novel approach for pretraining robotic manipulation Vision-Language-Action (VLA) models using a large corpus of unscripted real-life video recordings of human…
UniGraspTransformer: Simplified Policy Distillation for Scalable Dexterous Robotic Grasping
Wenbo Wang, Fangyun Wei, Lei Zhou +9
We introduce UniGraspTransformer, a universal Transformer-based network for dexterous robotic grasping that simplifies training while enhancing scalability and performance. Unlike…
CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation
Qixiu Li, Yaobo Liang, Zeyu Wang +15
The advancement of large Vision-Language-Action (VLA) models has significantly improved robotic manipulation in terms of language-guided task execution and generalization to unseen…