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Every Token Counts: Exact Likert-Scale Distributions for Measuring LLM Attitudes and Biases

Wadi, Davood et al.
arXiv (All) · Papers
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computation-and-language
As Large Language Models (LLMs) are increasingly deployed as autonomous agents, accurately evaluating their latent values and biases is critical. The NLP community typically evaluates models using large, unstructured benchmarks. While effective for general capabilities, these datasets fundamentally
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