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Aligning Language Model Benchmarks with Pairwise Preferences

Gutierrez, Marco et al.
arXiv (All) · Papers
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artificial-intelligencecomputation-and-language
Language model benchmarks are pervasive and computationally-efficient proxies for real-world performance. However, many recent works find that benchmarks often fail to predict real utility. Towards bridging this gap, we introduce benchmark alignment, where we use limited amounts of information about
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