arxivstat.MLcs.AIcs.LGstat.AP2026-07-16
Design-Based Supervised Learning with Noisy Human Labels
Robert Chew, Matthew R. Williams
Researchers increasingly use automated classifiers to label unstructured data for statistical analysis. Existing rectification methods can correct errors in these automated labels using a probability-sampled audit set, but they usually treat the audit labels as correct. In practi…