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Optimal Transport Reweighting for Robust Learning under Spurious Correlations and Label Noise
Machine learning models often suffer performance degradation under subpopulation shift, particularly when spurious correlations cause models to rely on shortcut features that fail to generalize across subgroups. A recent line of work mitigates this issue by using loss-based signals to identify infor
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