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Northwestern University
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Human response time, often discarded, unlocks in-context adaptation to unseen preference domains for RLHF, outperforming standard transformers.
Forget reward model fitting: these primal-dual policy gradient methods offer provably safe and convergent RLHF in infinite horizon settings.