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GRIT: Out-of-Distribution Robustness from Finite and Noisy Invariant Pairs
Predictors often exploit spurious correlations that fail under distribution shift, undermining out-of-distribution (OOD) robustness. Invariant pairs, such as the same object photographed against different backgrounds, directly indicate which variation should not affect prediction. Yet real pair coll
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