collaborators
Showing cs.ROShow all

7 papers · 1 filter

cs.RO2026

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…

cs.RO2026

World Action Models: A Survey

Qiuhong Shen, Shihua Zhang, Yue Liao +5

World Action Models (WAMs) are embodied predictive-action models that make a forecast of the future available to action. Recent WAMs repurpose large video generation models, and a…

cs.RO2026

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…

cs.RO2025

Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

Yue Liao, Pengfei Zhou, Siyuan Huang +11

We introduce Genie Envisioner (GE), a unified world foundation platform for robotic manipulation that integrates policy learning, evaluation, and simulation within a single video-g…

cs.RO2025

RoboCerebra: A Large-scale Benchmark for Long-horizon Robotic Manipulation Evaluation

Songhao Han, Boxiang Qiu, Yue Liao +4

Recent advances in vision-language models (VLMs) have enabled instruction-conditioned robotic systems with improved generalization. However, most existing work focuses on reactive…

cs.RO2025

EWMBench: Evaluating Scene, Motion, and Semantic Quality in Embodied World Models

Hu Yue, Siyuan Huang, Yue Liao +5

Recent advances in creative AI have enabled the synthesis of high-fidelity images and videos conditioned on language instructions. Building on these developments, text-to-video dif…

cs.RO2025

EnerVerse-AC: Envisioning Embodied Environments with Action Condition

Yuxin Jiang, Shengcong Chen, Siyuan Huang +8

Robotic imitation learning has advanced from solving static tasks to addressing dynamic interaction scenarios, but testing and evaluation remain costly and challenging due to the n…