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Holdout Best-of-N: Unbiased Evaluation and Its Cost
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Shrey Shah, Yinheng Li

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ResearcharXiv cs.CL

Holdout Best-of-N: Unbiased Evaluation and Its Cost

arXiv:2610.08719v1 Announce Type: new Abstract: Reusing the scores that select a Best-of-$N$ winner can overstate its expected reward. We study evaluation from a fixed matrix of $K$ independent scores per candidate for a policy that selects using $J$ fresh scores. A single estimator based only on this matrix is exactly unbiased for expected judge reward under every independent, stable collection of candidate-specific score laws if and only if $J

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This story was published by arXiv cs.CL and written by Shrey Shah, Yinheng Li. SyncAI.news shows a preview; the complete article is on the publisher's site.

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