Optimized Labeling Resource Allocation for Prediction-Assisted Inference via OPAL

ArXi:2606.03211v1 Announce Type: cross Active Statistical Inference is a new framework to make precise claims about population parameters with provable statistical guarantees. It uses a predictive "black-box" machine learning (ML) model to strategically decide which data points to label, roughly prioritizing samples for which the ML model is unsure about their label values. A major issue is that the framework can be brittle when uncertainty estimates are noisy. This paper