A history-conditioned latent motion prior enables real-world dexterous hand policies to improve from 56% to 99% success via residual reinforcement learning without breaking contact.
Title resolution pending
1 Pith paper cite this work, alongside 468 external citations. Polarity classification is still indexing.
1
Pith paper citing it
468
external citations · OpenAlex
fields
cs.RO 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
LAMP: Latent Motion Prior-Guided Real-World Learning for Dexterous Hand Manipulation
A history-conditioned latent motion prior enables real-world dexterous hand policies to improve from 56% to 99% success via residual reinforcement learning without breaking contact.