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Generalization
Understanding Out-of-Distribution Accuracies through Quantifying Difficulty of Test Samples
Existing works show that although modern neural networks achieve remarkable generalization performance on the in-distribution (ID) dataset, the accuracy drops significantly on the out-of-distribution (OOD) datasets …
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