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VioLA: Learning Generalist Humanoid Control Policies from Human Data

Paper recorded by Signals 4 on 2026-10-08 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09

Category: cs.LG · 机器学习 · first seen 2026-10-09

Abstract

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-t

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#320 most recent of 749 cs.LG papers we have recorded · ↑ newer: Density Ratio Estimation with Stein Displacement Fields · ↓ older: FAITH: Feasibility-Aware Safety-Filtered RL for High-Dimensional Syste
Cite this page: VioLA: Learning Generalist Humanoid Control Policies from Human Data: the #320 most recent of 749 cs.LG papers we have recorded (as of 2026-10-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/viola-learning-generalist-humanoid-control-policies-from-human-data.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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