Combating Shortcut Learning for Robust Deep Models

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Explore the critical concept of generalization in deep learning, highlighting the challenge of shortcut learning and its effect on AI model robustness. Delve into reliance on superficial correlations and spurious data biases across domains like computer vision and NLP, and examine strategies such as dataset refinement and invariant risk minimization to address these issues. Conclude with key takeaways and future directions for improving AI fairness and reliability.