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Found 2 papers, 2 papers with code
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
While deep neural networks show great performance on fitting to the training distribution, improving the networks' generalization performance to the test distribution and robustness to the sensitivity to input perturbations still remain as a challenge.
Puzzle Mix: Exploiting Saliency and Local Statistics for Optimal Mixup
While deep neural networks achieve great performance on fitting the training distribution, the learned networks are prone to overfitting and are susceptible to adversarial attacks.
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