Post-hoc learning to defer is cast as density-ratio learning between model and expert ideal distributions, producing DR CPE losses that recover Chow's rule for KL-based ideals and support adjustable deferral via thresholding.
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Density-Ratio Losses for Post-Hoc Learning to Defer
Post-hoc learning to defer is cast as density-ratio learning between model and expert ideal distributions, producing DR CPE losses that recover Chow's rule for KL-based ideals and support adjustable deferral via thresholding.