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How Many Labels Does Model Choice Need? Certificates and Budgets for Selective Prediction
Classifiers can make identical predictions yet require labels to compare their selective performance: confidence ranks weight the same errors differently. We quantify this requirement for the area under the generalized risk-coverage curve (AUGRC). A prelabel lower bound rules out insufficient budget
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