AINeutralarXiv – CS AI · 10h ago6/10
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RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation
Researchers introduce RARM (Reference-Anchored Reward Model), a visual AI system that solves a major bottleneck in robot learning by converting single successful demonstrations into dense reward signals without task-specific engineering. The approach uses confidence-gated progress matching to avoid false-positive rewards, achieving superior performance across simulated and real-world manipulation tasks.