Gives non-adaptive O(log n)-approximation for matroid basis certification under arbitrary correlations, tight unless P=NP, plus O(log k) adaptive for k-uniform matroids in vertex-induced graph probing.
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Global Bradley-Terry rankings of LLMs are misleading due to structured heterogeneity in user preferences, and small (λ, ν)-portfolios recover coherent subpopulations that cover over 96% of votes with just five rankings.
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Stochastic Function Certification with Correlations
Gives non-adaptive O(log n)-approximation for matroid basis certification under arbitrary correlations, tight unless P=NP, plus O(log k) adaptive for k-uniform matroids in vertex-induced graph probing.
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Why Global LLM Leaderboards Are Misleading: Small Portfolios for Heterogeneous Supervised ML
Global Bradley-Terry rankings of LLMs are misleading due to structured heterogeneity in user preferences, and small (λ, ν)-portfolios recover coherent subpopulations that cover over 96% of votes with just five rankings.