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arXiv:2305.18339 (cs)
[Submitted on 25 May 2023 (v1), last revised 30 Jul 2023 (this version, v2)]

Title:A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutions

Authors:Yuntao Wang, Yanghe Pan, Miao Yan, Zhou Su, Tom H. Luan
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Abstract:With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift in content creation and knowledge representation. AIGC uses generative large AI algorithms to assist or replace humans in creating massive, high-quality, and human-like content at a faster pace and lower cost, based on user-provided prompts. Despite the recent significant progress in AIGC, security, privacy, ethical, and legal challenges still need to be addressed. This paper presents an in-depth survey of working principles, security and privacy threats, state-of-the-art solutions, and future challenges of the AIGC paradigm. Specifically, we first explore the enabling technologies, general architecture of AIGC, and discuss its working modes and key characteristics. Then, we investigate the taxonomy of security and privacy threats to AIGC and highlight the ethical and societal implications of GPT and AIGC technologies. Furthermore, we review the state-of-the-art AIGC watermarking approaches for regulatable AIGC paradigms regarding the AIGC model and its produced content. Finally, we identify future challenges and open research directions related to AIGC.
Comments: 20 pages, 6 figures, 4 tables
Subjects: Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Computation and Language (cs.CL)
Cite as: arXiv:2305.18339 [cs.CY]
  (or arXiv:2305.18339v2 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2305.18339
arXiv-issued DOI via DataCite
Related DOI: https://doi.org/10.1109/OJCS.2023.3300321
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Submission history

From: Yuntao Wang [view email]
[v1] Thu, 25 May 2023 15:09:11 UTC (1,287 KB)
[v2] Sun, 30 Jul 2023 02:31:58 UTC (4,721 KB)
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