Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation

arXiv:2403.12075v1 Announce Type: cross
Abstract: With the rise of text-to-image (T2I) generative AI models reaching wide audiences, it is critical to evaluate model robustness against non-obvious attacks to mitigate the generation of offensive images. By focusing on ``implicitly adversarial'' prompts (those that trigger T2I models to generate unsafe images for non-obvious reasons), we isolate a set of difficult safety issues that human creativity is well-suited to uncover. To this end, we built the Adversarial Nibbler Challenge, a red-teaming methodology for …

abstract adversarial ai models arxiv attacks cs.ai cs.cr cs.cv cs.cy cs.lg diverse generate generative generative ai models image image generation images model robustness prompts robustness text text-to-image type