AI RESEARCH
Prediction-Powered Conditional Inference
arXiv CS.LG
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ArXi:2603.05575v1 Announce Type: cross We study prediction-powered conditional inference in the setting where labeled data are scarce, unlabeled covariates are abundant, and a black-box machine-learning predictor is available. The goal is to perform statistical inference on conditional functionals evaluated at a fixed test point, such as conditional means, without imposing a parametric model for the conditional relationship. Our approach combines localization with prediction-based variance reduction. First, we.