Reproduce “Instance-Optimal Estimation with Multiple LLM Judges on a Budget” on OpenResearch

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About this paper

Junghyun Lee, Sanghwa Kim, Yassir Jedra, Alexandre Proutière, Se-Young Yun

The authors allocate a fixed query budget across judges and prompt–response pairs by estimating pair–judge score variances and favoring better cost–reliability trade-offs. Adaptive allocation lowers L2 error than uniform allocation in shown experiments. Theoretically, it matches the oracle’s leading error rate for bounded, unbiased scores with known judge costs and a shared true score per pair.

Summary by alphaXiv.

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