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VioLA: Learning Generalist Humanoid Control Policies from Human Data

L5 · ResearcherResearcharXiv· 10/8/2026

Presents a novel robotics architecture that enables transfer learning from abundant human data to robot control without task-specific fine-tuning.

AI Summary

VioLA trains humanoid control policies using human motion data by predicting motion latents that work for both humans and robots, achieving 100% zero-shot locomotion success on real hardware.

Excerpt

Teaching a humanoid to follow instructions with its whole body runs into two obstacles. Its action space is large and tightly coupled: legs, arms, and fingers must move together while the robot keeps its balance, which makes joint-level actions hard to learn. And humanoid demonstrations are scarce, so current humanoid generalist policies do not follow new instructions out of the box and are fine-tuned on teleoperated demonstrations of each task before deployment. Human demonstrations exist in fa

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