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Shortcuts, also described as Clever Hans behavior, spurious correlations, or confounders, present a significant challenge in machine learning and AI, critically affecting model generalization and robustness.
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Discovery of a Generalization Gap of Convolutional Neural Networks on COVID-19 X-Rays Classification
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Beyond question-based biases: Assessing multimodal shortcut learning in visual question answering. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 1574–1583
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AI for radiographic COVID-19 detection selects shortcuts over signal
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Roses are red, violets are blue… but should vqa expect them to?. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 2776–2785
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Learning debiased representation via disentangled feature augmentation
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Rectifying the shortcut learning of background for few-shot learning
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SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency. In The Eleventh International Conference on Learning Representations, ICLR 2023, Kigali, Rwanda, May 1-5, 2023 . OpenReview.net
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Uncovering and correcting shortcut learning in machine learning models for skin cancer diagnosis
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Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement
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Right for better reasons: Training differentiable models by constraining their influence functions. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 35. 9533–9540
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