Record summary
A quick snapshot of what this page covers.
Risk profile
How this risk is described and categorized.
"Adversarial training can be affected by robust overfitting, where the model’s robustness on test data decreases during further training, particularly after the learning rate decay. This issue has been consistently observed across various datasets and algorithms in adversarial training settings [163, 230]. Robust over- fitting can affect the model’s ability to generalize effectively and reduce its resilience to adversarial attacks."
Suggested mitigations
Defenses that may help with related attacks.
Source
Research source for this risk, when available.
Included resource
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems
Original source
MIT AI Risk Repository
Open the public repository used for AI risk records and taxonomy fields.
