spurious correlation
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness
Results averaged over ResNet18 and ResNet50.
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Jun Wang
With the success of deep learning, there are growing concerns over interpretability (Lipton, 2018). Ideally, the explanation should be both faithful (reflecting the model's actual behavior) and plausible
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CODA: A Correlation-Oriented Disentanglement and Augmentation Modeling Scheme for Better Resisting Subpopulation Shifts
Data-driven models learned often struggle to generalize due to widespread subpopulation shifts, especially the presence of both spurious correlations and group imbalance (SC-GI).
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DeNetDM: Debiasing by Network Depth Modulation
Neural networks trained on biased datasets tend to inadvertently learn spurious correlations, hindering generalization.
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Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
Please refer to the website for more details.
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