[41] Graeme S. Halford, William H. Wilson, Jian Guo, Ross W. Gayler, Janet Wiles, and J. E. M. Stewart. Connectionist Implications for Processing Capacity Limitations in Analogies, pages 363-415. Ablex Publishing, 1994.
[42] Douglas R. Hofstadter. Fluid Concepts and Creative Analogies: Computer Models of the Fundamental Mechanisms of Thought. Basic Books, 1995.
[43] Stefan Depeweg, Constantin A. Rothkopf, and Frank Jäkel. Solving Bongard Problems with a Visual Language and Pragmatic Reasoning. CoRR, abs/1804.04452, 2018.
[44] Chi Zhang, Feng Gao, Baoxiong Jia, Yixin Zhu, and Song-Chun Zhu. RAVEN: A Dataset for Relational and Analogical Visual rEasoNing. CoRR, abs/1903.02741, 2019.
[45] Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, and Timothy Lillicrap. Learning to Make Analogies by Contrasting Abstract Relational Structure. CoRR, abs/1902.00120, 2019.
[46] Scott E. Reed, Yi Zhang, Yuting Zhang, and Honglak Lee. Deep Visual Analogy-Making. In C. Cortes, N. Lawrence, D. Lee, M. Sugiyama, and R. Garnett, editors, Advances in Neural Information Processing Systems, volume 28. Curran Associates, Inc., 2015.
[47] Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei A. Efros. Visual Prompting via Image Inpainting. CoRR, abs/22098.00647, 2022.
[48] Yilun Du, Shuang Li, and Igor Mordatch. Compositional Visual Generation with Energy Based Models. In H. Larochelle, M. Ranzato, R. Hadsell, M.F. Balcan, and H. Lin, editors, Advances in Neural Information Processing Systems, volume 33, pages 6637-6647. Curran Associates, Inc., 2020.
[49] Nan Liu, Shuang Li, Yilun Du, Antonio Torralba, and Joshua B. Tenenbaum. Compositional Visual Generation with Composable Diffusion Models. CoRR, abs/2206.01714, 2022.
[50] Yilun Du, Shuang Li, Yash Sharma, Joshua B. Tenenbaum, and Igor Mordatch. Unsupervised Learning of Compositional Energy Concepts. CoRR, abs/2111.03042, 2021.
[51] Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-Or. Prompt-to-Prompt Image Editing with Cross Attention Control. CoRR, abs/2208.01626, 2022.
[52] Dani Valevski, Matan Kalman, Yossi Matias, and Yaniv Leviathan. UniTune: Text-Driven Image Editing by Fine Tuning an Image Generation Model on a Single Image. CoRR, abs/2210.09477, 2022.
[53] Bahjat Kawar, Shiran Zada, Oran Lang, Omer Tov, Huiwen Chang, Tali Dekel, Inbar Mosseri, and Michal Irani. Imagc: Text-Based Real Image Editing with Diffusion Models. CoRR, abs/2210.09276, 2022.
[54] Anirudh Goyal, Alex Lamb, Jordan Hoffmann, Shagun Sodhani, Sergey Levine, Yoshua Bengio, and Bernhard Schölkopf. Recurrent Independent Mechanisms. CoRR, abs/1909.10893, 2020.
[55] Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, and Michael Mozer. Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems. CoRR, abs/2006.16225, 2020.
[56] Anirudh Goyal, Aniket Didolkar, Nan Rosemary Ke, Charles Blundell, Philippe Beaudoin, Nicolas Heess, Michael Mozer, and Yoshua Bengio. Neural Production Systems: Learning Rule-Governed Visual Dynamics. CoRR, abs/2103.01937, 2022.
[57] Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Anirudh Goyal, Jorg Bornschein, Melanie Rey, Theophane Weber, Matthew Botvinic, Michael Mozer, and Danilo Jimenez Rezende. Learning to Induce Causal Structure. CoRR, abs/2204.04875, 2022.
[58] Snap Inc. Bitmoji. https://www.bitmoji.com/, accessed 2023.
[59] Shivam Garg, Dimitris Tsipras, Percy Liang, and Gregory Valiant. What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. CoRR, abs/2208.01066, 2022.