CoREN uses an LLM offline to estimate dense action rewards, filters them through three consistency checks, and aligns them to sparse success labels to train a small offline RL agent for household instruction-following tasks.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.AI 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
LLM-Based Offline Learning for Embodied Agents via Consistency-Guided Reward Ensemble
CoREN uses an LLM offline to estimate dense action rewards, filters them through three consistency checks, and aligns them to sparse success labels to train a small offline RL agent for household instruction-following tasks.