Learning Stable Predictors from Weak Supervision under Distribution Shift
arXiv:2604.05002v1 Announce Type: cross
Abstract: Learning from weak or proxy supervision is common when ground-truth labels are unavailable, yet robustness under distribution shift remains poorly understood, especially when the supervision mechanism …