Hydra-0: Action Flow for Generalist World Modeling and Control
Summary
Hydra-0 introduces action flow as a shared visual interface for generalist world modeling and robot control, achieving significant error reductions and enabling zero-shot composition across diverse embodiments.
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Paper page - Hydra-0: Action Flow for Generalist World Modeling and Control
Source: https://huggingface.co/papers/2608.18077 Authors:
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Abstract
Hydra-0 uses action flow as a shared visual interface for generalist world modeling and robot control across diverse embodiments and tasks.
We introduce Hydra-0, a generalistworld modelconditioned onaction flow, which represents robot actions aspixel motion. This shared visual interface enables generalistworld modeling and control by learning action consequences across embodiments, tasks, environments, and video-generation backbones. Our best configuration achieves 90.4% lower robot-motion error and 60.2% lower object-motion error than our action-conditioned baseline, while supportingzero-shot compositionand data-efficient adaptation. On the RoboLab benchmark, Hydra-0 achieves a Pearson correlation of r=0.96 between replayed and reference success rates. Finally, we uncover an emergentinverse modeof this interface: aworld action modelthat predicts compatible robot motion from desired object flow transferred from a human demonstration. A trained action head maps the resulting latent features to executable actions without requiring task-specific expert robot demonstrations. Together, these results demonstrate the potential ofaction flowas a shared control interface connecting heterogeneous training data,open-loop policy evaluation, and robot control.
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