uar-unforeseen-attack-robustness--23d4b7c9·1 events·first seen Aliases: UAR (Unforeseen Attack Robustness)
OpenAI published a method to evaluate whether neural network classifiers can defend against adversarial attacks not encountered during training. The approach introduces a new metric called UAR (Unforeseen Attack Robustness) to quantify a model's resilience to unanticipated attacks. The work argues for measuring robustness across a broader, more diverse set of attack types rather than only those seen in training.