Abdullah08/AsymmetricAttack

Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks This repository implements the concepts from the paper "Asymmetric Bias in Text-to-Image Generation with Adversarial Attacks." The study examines adversarial attacks on Text-to-Image (T2I) models like Stable Diffusion, introducing entity swapping via adversarial suffixes and gradient-based attacks. It reveals asymmetric attack success rates (ASRs) and proposes probing metrics to predict vulnerabilities based on model biases.… See the full description on the dataset page: https://huggingface.co/datasets/Abdullah08/AsymmetricAt

<iframe src="https://silytics.si/embed/item/f60a3919-c8d9-4ce7-a843-d4d7eb8a4bfd" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 16 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.