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Found 5 papers, 0 papers with code
Towards Scalable and Robust Model Versioning
In this paper, we explore the feasibility of generating multiple versions of a model that possess different attack properties, without acquiring new training data or changing model architecture.
A Two-stage Personalized Virtual Try-on Framework with Shape Control and Texture Guidance
The Diffusion model has a strong ability to generate wild images.
Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models
In this paper, we show that poisoning attacks can be successful on generative models.
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker
Finding classifiers robust to adversarial examples is critical for their safe deployment.
On the Privacy-Utility Tradeoff in Peer-Review Data Analysis
The crux of the framework lies in recognizing that a part of the data pertaining to the reviews is already available in public, and we use this information to post-process the data released by any privacy mechanism in a manner that improves the accuracy (utility) of the data while retaining the privacy guarantees.
