Learning Stable Predictors from Weak Supervision under Distribution Shift
arXiv:2604.05002v1 Announce Type: new Abstract: Learning from weak or proxy supervision is common when ground-truth labels are unavailable, yet robustness under distribution shift remains poorly …
Mehrdad Shoeibi, Elias Hossain, Ivan Garibay, Niloofar Yousefi
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