1. Cao, Y., Li, S., Liu, Y., Yan, Z., Dai, Y., Yu, P.S., and Sun, L. (2023). A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt. arXiv.
2. Zhang, C., Zhang, C., Zheng, S., Qiao, Y., Li, C., Zhang, M., Dam, S., Myaet Thwal, C., Tun, Y.L., and Huy, L. (2023). A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?. arXiv.
3. (2023, June 29). Generative AI Market Size to Hit around USD 118.06 Bn by 2032. Available online: https://www.globenewswire.com/en/news-release/2023/05/15/2668369/0/en/Generative-AI-Market-Size-to-Hit-Around-USD-118-06-Bn-By-2032.html/.
4. Karras, T., Laine, S., and Aila, T. (2019, January 15–20). A style-based generator architecture for generative adversarial networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA.
5. Language models are few-shot learners;Brown;Adv. Neural Inf. Process. Syst.,2020