Robot policies trained on human interventions that rewind to a familiar state and then correct the mistake achieve higher long-horizon success and better data efficiency than imitation on full demonstrations alone.
Genie centurion: Accelerating scalable real-world robot training with human rewind-and-refine guidance, 2025
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.RO 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
support 1representative citing papers
citing papers explorer
-
RaC: Robot Learning for Long-Horizon Tasks by Scaling Recovery and Correction
Robot policies trained on human interventions that rewind to a familiar state and then correct the mistake achieve higher long-horizon success and better data efficiency than imitation on full demonstrations alone.