Shortcut Learning

A widely observed phenomenon in deep learning where a model exploits surface-level statistical correlations in training data that are associated with labels but semantically irrelevant. Models exhibiting shortcut learning perform well on in-distribution data but fail to generalize to out-of-distribution scenarios.