4 papers
GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation
AgiBot Research Team, Renhang Liu, Wenzhi Zhao +42
World-action models (WAM) predict future states to guide robot actions, enabling learning from both action-free video and action-labeled interaction. Most inherit pretrained video…
RoboClaw: An Agentic Framework for Scalable Long-Horizon Robotic Tasks
Ruiying Li, Yunlang Zhou, YuYao Zhu +15
Vision-Language-Action (VLA) systems have shown strong potential for language-driven robotic manipulation. However, scaling them to long-horizon tasks remains challenging. Existing…
Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training
Yi Liu, Sukai Wang, Dafeng Wei +10
General-purpose robotic systems operating in open-world environments must achieve both broad generalization and high-precision action execution, a combination that remains challeng…
Why Tree-Style Branching Matters for Thought Advantage Estimation in GRPO
Hongcheng Wang, Yinuo Huang, Sukai Wang +2
Group Relative Policy Optimization (GRPO) trains Chain-of-Thought reasoning with verifiable rewards, but estimating thought-level advantages without value functions often suffers f…