Active Learning with Imperfect Labels: Optimal Labeler Assignment and Sample Selection.

arXiv:2512.12870v2 Announce Type: replace-cross Abstract: Active Learning (AL) is commonly used in applications where labeling data is expensive or time-consuming. In practice, however, labels are often noisy due to varying labeler expertise and annotation unc