How Many Humans Are 32 LLM Judges Worth?
A panel's human-equivalent size is target-specific. Matching a fixed 32-judge panel to empirical human label distributions on three ChaosNLI tasks yields two distinct effective sizes: distributional-error matching gives $ν_{\mathrm{MSE}}=2.304$, $3.750$, and $3.445$, whereas spectral matching gives $ν_H=4.242$, $6.459$, and $6.499$, a gap of $1.72$--$1.89\times$; a binary-error diagnostic credits the same panels with only $1.971$--$2.227$ effective votes. Extrapolating the distributional-error curve at fixed squared mean residual, mean member variance, and normalized mean covariance gives asymptotes of $2.392$, $3.990$, and $3.655$, with 32 judges already reaching $94.0$--$96.3\%$. An exa...
| Authors | Chao Li, Yingying Yu, Yunfeng Li |
|---|---|
| Primary category | cs.CL |
| Published | 18 September 2026 |
| Last updated at source | 24 September 2026 |
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