adversarial-example

Adversarial examples are inputs to models that have been intentionally modified to cause the model to make a mistake. These inputs are often generated by adding small, imperceptible perturbations to legitimate data points. The study of adversarial examples is crucial for understanding the vulnerabilities of machine learning systems and improving their robustness against potential attacks.