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Low-Rank Adaptation for Critic Learning in Off-Policy Reinforcement Learning
Low-rank adaptation regularizes critic learning by constraining updates to low-dimensional subspaces via frozen base weights, reducing loss and improving off-policy RL performance.
Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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AI panel: 7 of 20 reviewers recommend it
lenient 4/5
medium 3/10
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