10 papers · 1 filter
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…
GE-Sim 2.0: A Roadmap Towards Comprehensive Closed-loop Video World Simulators for Robotic Manipulation
Boxiang Qiu, Liliang Chen, Yue Liao +12
We introduce GE-Sim 2.0 (Genie Envisioner World Simulator 2.0), a closed-loop video world simulator for robotic manipulation. Building on the action-conditioned video generation fr…
Act2Goal: From World Model To General Goal-conditioned Policy
Pengfei Zhou, Liliang Chen, Shengcong Chen +5
Specifying robotic manipulation tasks in a manner that is both expressive and precise remains a central challenge. While visual goals provide a compact and unambiguous task specifi…
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…
Real2Edit2Real: Generating Robotic Demonstrations via a 3D Control Interface
Yujie Zhao, Hongwei Fan, Di Chen +5
Recent progress in robot learning has been driven by large-scale datasets and powerful visuomotor policy architectures, yet policy robustness remains limited by the substantial cos…
Fidelity-Aware Data Composition for Robust Robot Generalization
Zizhao Tong, Di Chen, Sicheng Hu +6
Generalist robot policies trained on large-scale, visually homogeneous datasets can be susceptible to shortcut learning, which impairs their out-of-distribution (OOD) generalizatio…