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Rarity Determines Minimax Rates of Semantic Entropy From Weak Pairwise Judgments With a Known Channel
The semantic entropy of a language model is the entropy of the meanings of its sampled answers. The meanings are never observed, and the entropy is estimated from the verdicts of a pairwise equivalence judge. Given the meanings of $n$ answers, a known channel declares each pair equivalent independen
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