arxiv
PublishedMay 26, 2026 at 4:00 AM
—neutral
Quantifying Empirical Compute-Supervision Tradeoffs in RLVR
Publisher summary· verbatim
arXiv:2605.25252v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for post-training language models, but in practice, verifiers are rarely perfect. Recent theoretical work predicts that verifier noise affects the rate of learning b
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Originally published on arxiv ↗