10 papers
VITAL: From Visual Motion to Precise Action
Ao Liang, Youquan Liu, Mingxiao Li +7
World-action models aim to turn visual anticipation into driving decisions, yet typically train action experts on trajectory representations defined independently of visual dynamic…
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…
Quo Vadis, World Modeling?
Yu Yang, Xuemeng Yang, Licheng Wen +17
Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow, unsafe, and hard to paralleliz…
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…
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…
SPIRAL: Self-Evolving Action-Conditioned Video Generation via Reflective Planning Agents
Yu Yang, Yue Liao, Jianbiao Mei +11
Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended horizons, requiring procedural…
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…
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…
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…
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…