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From tests to effect sizes: Quantifying uncertainty and statistical variability in multilingual and multitask NLP evaluation benchmarks
Jonne S\"alev\"a, Duygu Ataman, Constantine Lignos
https://arxiv.org/abs/2509.22612

From tests to effect sizes: Quantifying uncertainty and statistical variability in multilingual and multitask NLP evaluation benchmarks
In this paper, we introduce a set of resampling-based methods for quantifying uncertainty and statistical precision of evaluation metrics in multilingual and/or multitask NLP benchmarks. We show how experimental variation in performance scores arises from both model- and data-related sources, and that accounting for both of them is necessary to avoid substantially underestimating the overall variability over hypothetical replications. Using multilingual question answering, machine translation, …

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