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pro vyhledávání: '"Guo, Moyang"'
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 methods can be broadly categorized into passive and watermark-based approach
Externí odkaz:
http://arxiv.org/abs/2411.13553
Generative AI raises many societal concerns such as boosting disinformation and propaganda campaigns. Watermarking AI-generated content is a key technology to address these concerns and has been widely deployed in industry. However, watermarking is v
Externí odkaz:
http://arxiv.org/abs/2407.04086
The increasing realism of synthetic speech, driven by advancements in text-to-speech models, raises ethical concerns regarding impersonation and disinformation. Audio watermarking offers a promising solution via embedding human-imperceptible watermar
Externí odkaz:
http://arxiv.org/abs/2406.06979
Watermark has been widely deployed by industry to detect AI-generated images. A recent watermarking framework called \emph{Stable Signature} (proposed by Meta) roots watermark into the parameters of a diffusion model's decoder such that its generated
Externí odkaz:
http://arxiv.org/abs/2405.07145
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) service who created a given piece of AI-generated content--remains larg
Externí odkaz:
http://arxiv.org/abs/2404.04254
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 settings is well understood in the literature. However, the robustnes
Externí odkaz:
http://arxiv.org/abs/2403.15365
Autor:
Guo Moyang
Publikováno v:
SHS Web of Conferences, Vol 180, p 03017 (2023)
In the rapidly evolving organizational landscape of the 21st century, traditional motivational strategies are increasingly inadequate. This paper explores the application of Self-Determination Theory (SDT) as an alternative framework for understandin
Externí odkaz:
https://doaj.org/article/abdf6f0760d54e59a49f543a34711b9b
