Separating Shortcut Transition from Cross-Family OOD Failure in a Minimal Model
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Abstract (arXiv)
Shortcut features are often invoked to explain out-of-distribution (OOD) failure, but training correlation, learned shortcut use, and test-time failure need not coincide. We study a minimal binary model with one invariant coordinate and one family-dependent shortcut coordinate. In the deterministic regime, positive average shortcut correlation pulls logistic ERM toward positive shortcut weight, but ridge regularization keeps the classifier invariant-dominated and prevents deterministic OOD failure. When the invariant coordinate is noisy, ridge-logistic ERM switches to the shortcut rule once the training shortcut signal exceeds the invariant signal. Whether that transition causes failure depends on the held-out family: weaker shortcut correlation yields positive excess risk, and sign-flipped families yield above-chance error. Synthetic checks match these analytic regimes and show that the same training-side transition can have different held-out consequences. The model separates shortcut attraction, shortcut-rule transition, and cross-family OOD failure.
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References · 12
- 2015Domain-Adversarial Training of Neural Networkscited by 3,023
- 2020Shortcut Learning in Deep Neural Networkscited by 1,928
- 2019Invariant Risk Minimizationcited by 1,832
- 2020WILDS: A Benchmark of in-the-Wild Distribution Shiftscited by 1,366
- 2019Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalizationcited by 1,232
- 2016Deep CORAL: Correlation Alignment for Deep Domain Adaptationcited by 1,194
- 2020In Search of Lost Domain Generalizationcited by 1,042
- 2020Out-of-Distribution Generalization via Risk Extrapolation (REx)cited by 737
- 2015Causal inference using invariant prediction: identification and confidence intervalscited by 533
- 2020The Risks of Invariant Risk Minimizationcited by 262
- 2020Learning from Failure: Training Debiased Classifier from Biased Classifiercited by 133
- 2021Does Invariant Risk Minimization Capture Invariance?cited by 116
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