[24] Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell, and Yacine Jernite. Stable bias: Analyzing societal representations in diffusion models. arXiv preprint arXiv:2303.11408, 2023.
[25] Leland McInnes, John Healy, and James Melville. UMAP: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426, 2018.
[26] Raphaël Millière. Adversarial attacks on image generation with made-up words. arXiv preprint arXiv:2208.04135, 2022.
[27] Changhoon Oh, Jungwoo Song, Jinhan Choi, Seonghyeon Kim, Sungwoo Lee, and Bongwon Suh. I lead, you help but only with enough details: Understanding user experience of CoCreation with artificial intelligence. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, number Paper 649 in CHI '18, pages 1-13, New York, NY, USA, April 2018. Association for Computing Machinery.
[28] Jonas Oppenlaender. The creativity of text-to-image generation. In Proceedings of the 25th International Academic Mindtrek Conference, Academic Mindtrek '22, pages 192-202, New York, NY, USA, November 2022. Association for Computing Machinery.
[29] Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov. Editing implicit assumptions in Text-to-Image diffusion models. arXiv preprint arXiv:2303.08084, 2023.
[30] Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, and Zaid Harchaoui. MAUVE scores for generative models: Theory and practice. arXiv preprint arXiv:2212.14578, 2022.
[31] Giada Pistilli, Carlos Munoz Ferrandis, Yacine Jernite, and Margaret Mitchell. Stronger together: on the articulation of ethical charters, legal tools, and technical documentation in ML. arXiv preprint arXiv:2305.18615, 2023.
[32] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. Learning transferable visual models from natural language supervision. In Proceedings of the 38th International Conference on Machine Learning, pages 8748-8763, 2021.
[33] Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. Zero-shot text-to-image generation. In Proceedings of the 38th International Conference on Machine Learning, volume 139, pages 8821-8831, 2021.
[34] Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, and Florian Tramère. Red-Teaming the Stable Diffusion safety filter. arXiv preprint arXiv:2210.04610, 2022.
[35] Samuel Rhys Cox, Yunlong Wang, Ashraf Abdul, Christian von der Weth, and Brian Y. Lim. Directed diversity: Leveraging language embedding distances for collective creativity in crowd ideation. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, number Article 393 in CHI '21, pages 1-35, New York, NY, USA, May 2021. Association for Computing Machinery.
[36] Robertson, Jean, McDaniel, and Craig. Themes of contemporary art : visual art after 1980. cir.nii.ac.jp, 2013.
[37] Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. High-resolution image synthesis with latent diffusion models. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 10684-10695, 2022.
[38] Kevin Roose. An AI-generated picture won an art prize. artists aren't happy. The New York times, 2(September), 2022.
[39] Simo Ryu. LoRA: Using low-rank adaptation to quickly fine-tune diffusion models. https://github.com/cloneofsimo/lora.