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Learning Adaptable Dexterous Skills via Hybrid Dexterous Mimicking

Paper recorded by Signals 4 on 2026-10-20 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-20 on arXiv · recorded by Signals 4 on 2026-10-21

Category: cs.LG · 机器学习 · first seen 2026-10-21

Abstract

Dexterous multi-finger hands hold promise to unlock diverse skills like functional grasps, in-hand reorientation, and dynamic handover that the human-designed world assumes, yet existing learning recipes force a trade-off. Goal-reaching reinforcement learning generalizes to arbitrary object poses but, lacking any human prior, converges to unnatural and unreliable finger strategies; motion tracking

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#219 most recent of 749 cs.LG papers we have recorded · ↑ newer: Agent Behavior Maps: Locating Agents by What They Would Do, Without Ru · ↓ older: Planning under Noise with Neural Operators
Cite this page: Learning Adaptable Dexterous Skills via Hybrid Dexterous Mimicking: the #219 most recent of 749 cs.LG papers we have recorded (as of 2026-10-20). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-adaptable-dexterous-skills-via-hybrid-dexterous-mimicking.html
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