19 citations · 50 across the 12 of their papers we have counts for
6 papers · 1 filter
Somesite I Used To Crawl: Awareness, Agency and Efficacy in Protecting Content Creators From AI Crawlers
Enze Liu, Elisa Luo, Shawn Shan +3
The success of generative AI relies heavily on training on data scraped through extensive crawling of the Internet, a practice that has raised significant copyright, privacy, and e…
Understanding Implosion in Text-to-Image Generative Models
Wenxin Ding, Cathy Y. Li, Shawn Shan +2
Recent works show that text-to-image generative models are surprisingly vulnerable to a variety of poisoning attacks. Empirical results find that these models can be corrupted by a…
Disrupting Style Mimicry Attacks on Video Imagery
Josephine Passananti, Stanley Wu, Shawn Shan +2
Generative AI models are often used to perform mimicry attacks, where a pretrained model is fine-tuned on a small sample of images to learn to mimic a specific artist of interest.…
Inception Attacks: Immersive Hijacking in Virtual Reality Systems
Zhuolin Yang, Cathy Yuanchen Li, Arman Bhalla +2
Today's virtual reality (VR) systems provide immersive interactions that seamlessly connect users with online services and one another. However, these immersive interfaces also int…
Organic or Diffused: Can We Distinguish Human Art from AI-generated Images?
Anna Yoo Jeong Ha, Josephine Passananti, Ronik Bhaskar +4
The advent of generative AI images has completely disrupted the art world. Distinguishing AI generated images from human art is a challenging problem whose impact is growing over t…
Towards Scalable and Robust Model Versioning
Wenxin Ding, Arjun Nitin Bhagoji, Ben Y. Zhao +1
As the deployment of deep learning models continues to expand across industries, the threat of malicious incursions aimed at gaining access to these deployed models is on the rise.…