activity
20242026
most citedWatermark-based Attribution of AI-Generated Content

6 citations · 6 across the 1 of their papers we have counts for

collaborators

8 papers

cs.CR20266 cited

Watermark-based Attribution of AI-Generated Content

Zhengyuan Jiang, Moyang Guo, Yuepeng Hu +2

Several companies have deployed watermark-based detection to identify AI-generated content. However, attribution--the ability to trace back to the user of a generative AI (GenAI) s…

cs.CR2025

EditTrack: Detecting and Attributing AI-assisted Image Editing

Zhengyuan Jiang, Yuyang Zhang, Moyang Guo +1

In this work, we formulate and study the problem of image-editing detection and attribution: given a base image and a suspicious image, detection seeks to determine whether the sus…

cs.CR2025

VideoMarkBench: Benchmarking Robustness of Video Watermarking

Zhengyuan Jiang, Moyang Guo, Kecen Li +5

The rapid development of video generative models has led to a surge in highly realistic synthetic videos, raising ethical concerns related to disinformation and copyright infringem…

cs.CR2025

A Transfer Attack to Image Watermarks

Yuepeng Hu, Zhengyuan Jiang, Moyang Guo +1

Watermark has been widely deployed by industry to detect AI-generated images. The robustness of such watermark-based detector against evasion attacks in the white-box and black-box…

cs.CR2025

AI-generated Image Detection: Passive or Watermark?

Moyang Guo, Yuepeng Hu, Zhengyuan Jiang +4

While text-to-image models offer numerous benefits, they also pose significant societal risks. Detecting AI-generated images is crucial for mitigating these risks. Detection method…

cs.LG2024

AudioMarkBench: Benchmarking Robustness of Audio Watermarking

Hongbin Liu, Moyang Guo, Zhengyuan Jiang +2

The increasing realism of synthetic speech, driven by advancements in text-to-speech models, raises ethical concerns regarding impersonation and disinformation. Audio watermarking…