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Environment-Conditioned Tail Reweighting for Invariant Learning under Mixed Shifts
Out-of-distribution generalization becomes challenging when spurious correlations vary across environments while difficult or underrepresented samples remain insufficiently emphasized within them. Invariant learning and reweighting address complementary aspects of this mixed-shift problem, yet apply
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