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.
Jacobs and Hanna Wallach
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
Closure of the Perspective API exposes structural dependence on a single proprietary toxicity scorer, leaving non-updatable benchmarks and irreproducible results while risking continued reliance on closed LLMs.
citing papers explorer
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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.
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Bye Bye Perspective API: Lessons for Measurement Infrastructure in NLP, CSS and LLM Evaluation
Closure of the Perspective API exposes structural dependence on a single proprietary toxicity scorer, leaving non-updatable benchmarks and irreproducible results while risking continued reliance on closed LLMs.