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Two is better than one: A Collapse-free Multi-Reward RLIF Training Framework
A multi-reward RLIF framework combining cluster-voting and self-certainty rewards with GDPO normalization and KL-Cov regularization prevents collapse and matches supervised RLVR performance.
Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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AI panel: 10 of 20 reviewers recommend it
lenient 4/5
medium 6/10
strict 0/5