Our new paper analyzes the important ways AI systems organize the visual world differently from humans.
arXiv:2408. 00001v2 Announce Type: replace-cross Abstract: Visual diffusion models have revolutionized the field of creative AI, producing high-quality and diverse content.
By Wenhao Wang, Yifan Sun, Zongxin Yang, Zhengdong Hu, Zhentao Tan, Yi Yang
arXiv:2606. 28510v1 Announce Type: cross Abstract: Across social and online platforms, people are increasingly exposed to AI-generated images.
By Negar Kamali, Candice Rockell Gerstner, Jessica Hullman, Matthew Groh
OpenAI advances AI content provenance with Content Credentials, SynthID, and a verification tool to help people identify and trust AI-generated media.
arXiv:2504. 06138v3 Announce Type: replace-cross Abstract: Professional users need tools to help them gain actionable insights from large multimedia collections.
By Marcel Worring, Jan Zah\'alka, Stef van den Elzen, Maximilian T. Fischer, Daniel A. Keim
arXiv:2606. 14748v1 Announce Type: cross Abstract: We present the Membership Inference Test (MINT) Demo 2, a framework designed to improve transparency in machine learning training processes.
By Daniel DeAlcala, Gonzalo Mancera, Julian Fierrez, Aythami Morales, Ruben Tolosana, Ruben Vera-Rodriguez