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Improvement and adoption of generative machine learning models is rapidly accelerating, as exemplified by the popularity of LLMs (Large Language Models) for text, and diffusion models for image generation.
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W. X. Zhao et al., A survey of large language models , arXiv preprint arXiv:2303.18223 (2023)
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S. Alemohammad et al., Self-consuming generative models go mad , International Conference on Learning Representations (ICLR) (2024)
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Q. Bertrand et al., On the stability of iterative retraining of generative models on their own data , International Conference on Learning Representations (ICLR) (2024)
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H. Cao et al., A survey on generative diffusion models , IEEE Transactions on Knowledge and Data Engineering (2024)
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N. Carlini et al., Poisoning web-scale training datasets is practical , IEEE Symposium on Security and Privacy (SP), 2024
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2023
Cited alongside, same era.