76%Highly rated
?Highly ratedVote to see the score
Drift Q-Learning
DriftQL combines drift-based behavioral regularization with critic-driven policy improvement to generate high-value actions in one forward pass, outperforming diffusion and flow methods on D4RL and OGBench.
Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 1 on Hugging Face
– ReadersNo votes yet
10/20 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: 10 of 20 reviewers recommend it
lenient 3/5
medium 7/10
strict 0/5