Patent attributes
Example aspects of the present disclosure are directed to systems and methods that enable improved adversarial training of machine-learned models. An adversarial training system can generate improved adversarial training examples by optimizing or otherwise tuning one or hyperparameters that guide the process of generating of the adversarial examples. The adversarial training system can determine, solicit, or otherwise obtain a realism score for an adversarial example generated by the system. The realism score can indicate whether the adversarial example appears realistic. The adversarial training system can adjust or otherwise tune the hyperparameters to produce improved adversarial examples (e.g., adversarial examples that are still high-quality and effective while also appearing more realistic). Through creation and use of such improved adversarial examples, a machine-learned model can be trained to be more robust against (e.g., less susceptible to) various adversarial techniques, thereby improving model, device, network, and user security and privacy.