LLM assistant with citation grounding improves accuracy by 6% and review speed by 25.9% in a simulated study of default judgment review.
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2 Pith papers cite this work. Polarity classification is still indexing.
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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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AI Assistance for Human Review of Default Judgments
LLM assistant with citation grounding improves accuracy by 6% and review speed by 25.9% in a simulated study of default judgment review.
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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.