Summary
Generative artificial intelligence (AI) now produces text at scale, which creates urgent needs for trustworthy ways to identify and trace AI-generated content. This project advances watermarking, a family of methods that embed a hidden signal into generated text so it can be identified later, while keeping the text useful and natural. A major goal is to enable more reliable attribution than current approaches, including the ability to encode more than a single yes-or-no identifier so that content can be traced to a specific model, system, or authorized use. The project also strengthens resilie
