Collected sources and patterns will appear here. Add from search, explore, or the patterns library.
(Model, Dataset, AttackMethod) -> RobustModel
Train models on a dynamic blend of clean inputs and real-time generated adversarial examples to align optimization boundaries with perturbed variants.
Problem it solves
Models trained purely on clean distributions overfit to local decision boundaries and remain fragile to evasion attacks.
Consumes
Emits
The real projects this mechanism was found in. Attribution is the point — this is how the best teams actually do it.