Papers › Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation

Learning Robust Classifiers with Self-Guided Spurious Correlation Mitigation

6 May 2024arXiv:2405.03649archive 2025-07-28

Guangtao Zheng, Wenqian Ye, Aidong Zhang

Deep neural classifiers tend to rely on spurious correlations between spurious attributes of inputs and targets to make predictions, which could jeopardize their generalization capability. Training classifiers robust to spurious correlations typically relies on annotations of spurious correlations in data, which are often expensive to get. In this paper, we tackle an annotation-free setting and propose a self-guided spurious correlation mitigation framework. Our framework automatically constructs fine-grained training labels tailored for a classifier obtained with empirical risk minimization to improve its robustness against spurious correlations. The fine-grained training labels are formulated with different prediction behaviors of the classifier identified in a novel spuriousness embedding space. We construct the space with automatically detected conceptual attributes and a novel spuriousness metric which measures how likely a class-attribute correlation is exploited for predictions. We demonstrate that training the classifier to distinguish different prediction behaviors reduces its reliance on spurious correlations without knowing them a priori and outperforms prior methods on five real-world datasets.

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collect_dataset_info gtzheng/LBC/datasets/in9_data.py official repository ran no licence file found · pointer only · 081ace50b2afb20c · report
conv1x1 gtzheng/LBC/models/resnet.py official repository ran · our draft was wrong no licence file found · pointer only · d9def42110729a85 · report
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find_classes gtzheng/LBC/datasets/in9_data.py official repository ran no licence file found · pointer only · 0ea0c32c88e93404 · report
get_correlated_features gtzheng/LBC/lbc_train.py official repository ran no licence file found · pointer only · 511d5c5ed80c997c · report
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get_transform_in gtzheng/LBC/datasets/inA_data.py official repository ran no licence file found · pointer only · 45146ddac421def6 · report
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