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The Flaw of Averages: Measuring Benchmark-Level Distributional Robustness
Benchmarks are central to measuring progress in language models, but aggregate scores can obscure substantial variation across subdomains, making models appear broadly competent despite concentrated strengths and weaknesses. We study this issue as benchmark-level distributional robustness: whether a
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