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Fake Artificial Intelligence Generated Contents (FAIGC): A Survey of Theories, Detection Methods, and Opportunities
May 3, 2024, 4:14 a.m. | Xiaomin Yu, Yezhaohui Wang, Yanfang Chen, Zhen Tao, Dinghao Xi, Shichao Song, Simin Niu
cs.CL updates on arXiv.org arxiv.org
Abstract: In recent years, generative artificial intelligence models, represented by Large Language Models (LLMs) and Diffusion Models (DMs), have revolutionized content production methods. These artificial intelligence-generated content (AIGC) have become deeply embedded in various aspects of daily life and work, spanning texts, images, videos, and audio. The authenticity of AI-generated content is progressively enhancing, approaching human-level creative standards. However, these technologies have also led to the emergence of Fake Artificial Intelligence Generated Content (FAIGC), posing new …
abstract aigc artificial artificial intelligence arxiv become contents cs.ai cs.cl cs.cy daily detection detection methods diffusion diffusion models embedded fake generated generative generative artificial intelligence intelligence language language models large language large language models life llms opportunities production survey type work
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