74%Highly rated
?Highly ratedVote to see the score
Reward-Conditioned Reinforcement Learning
RCRL conditions agents on reward parameterizations via replay counterfactual rewards, improving sample efficiency and enabling zero-shot behavioral adaptation without extra interaction.
Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026
– ReadersNo votes yet
9/20 AI panelreviewers recommend it
Readers and the AI panel: vote on this paper to see what they said.
Only vote on papers you've read. Sign in with GitHub to vote.
AI panel: 9 of 20 reviewers recommend it
lenient 4/5
medium 5/10
strict 0/5