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Found 3 papers, 2 papers with code
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
The surge in multimodal AI's success has sparked concerns over data privacy in vision-and-language tasks.
Improving Adversarial Transferability with Scheduled Step Size and Dual Example
Motivated by this finding, we argue that the information of adversarial perturbations near the benign sample, especially the direction, benefits more on the transferability.
How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies
Recent studies have shown that robustness (the ability for a model to perform well on unseen data) plays a significant role in the type of strategy that should be used when approaching a new problem and, hence, measuring the robustness of these strategies has become a fundamental problem.
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