Reproducibility study on how to find Spurious Correlations, Shortcut Learning, Clever Hans or Group-Distributional non-robustness and how to fix them

A reproducibility study unifies research on spurious correlations in deep neural networks across different domains, comparing correction methods including XAI-based approaches. The research finds that Counterfactual Knowledge Distillation (CFKD) most effectively improves model generalization, though practical deployment remains challenging due to group labeling dependencies and data scarcity issues.