Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization
Paper • 2608.26103 • Published • 25
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Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Paper • 2608.27550 • Published • 83 -
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning
Paper • 2608.27549 • Published • 49 -
Agentic Game Development as a Verifiable Trajectory Data Engine for Scaling World Models
Paper • 2608.25518 • Published • 59 -
The Imitator Game: Benchmarking Robot Imitative Ability Beyond Action Prediction
Paper • 2608.22301 • Published -
Fast-WAM: Do World Action Models Need Test-time Future Imagination?
Paper • 2603.16666 • Published • 2 -
SolarWM: Open Data and Scalable Training for Long-Horizon Video World Models
Paper • 2609.02886 • Published • 116 -
RoboTok: An Internet-Scale Data Engine for Human Demonstration Retrieval and Dexterous Manipulation Learning
Paper • 2609.03199 • Published • 30 -
ENPIRE: Agentic Robot Policy Self-Improvement in the Real World
Paper • 2606.19980 • Published • 15 -
GE-Act 2.0: Pretraining and Scaling a World-Action Model for Robotic Manipulation
Paper • 2609.05588 • Published • 56 -
Show-Harness: Just a VLM Agent Can Play Robots
Paper • 2609.10522 • Published • 160 -
Agent as Policy for Robotic Manipulation
Paper • 2609.12541 • Published • 17 -
Transferring the Intelligence of VLMs to Robotic Control
Paper • 2609.22966 • Published • 118 -
HuRo: Robotizing Human Videos for Scalable VLA Pretraining
Paper • 2609.10706 • Published • 29 -
In-Context Robot Learning with VLM Agents
Paper • 2609.19138 • Published • 29