Generated Content
Generated content (AIGC), encompassing AI-produced text, images, and video, is a rapidly evolving field focused on developing and evaluating methods for creating and identifying such content. Current research emphasizes improving the quality and realism of AIGC, developing robust detection methods to mitigate misuse (often employing techniques like CLIP and diffusion models), and exploring ethical considerations such as copyright and bias. This area is significant due to its potential to revolutionize creative industries and its implications for misinformation, intellectual property, and the broader societal impact of AI.
Papers
A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization
Tharindu Kumarage, Garima Agrawal, Paras Sheth, Raha Moraffah, Aman Chadha, Joshua Garland, Huan Liu
Towards Full Authorship with AI: Supporting Revision with AI-Generated Views
Jiho Kim, Ray C. Flanagan, Noelle E. Haviland, ZeAi Sun, Souad N. Yakubu, Edom A. Maru, Kenneth C. Arnold