[3] Shengnan An, Zeqi Lin, Qiang Fu, B. Chen, Nanning Zheng, Jian-Guang Lou, and D. Zhang. How do in-context examples affect compositional generalization? ArXiv, abs/2305.04835, 2023.
[4] Rim Assouel, Pau Rodriguez, Perouz Taslakian, David Vazquez, and Yoshua Bengio. Object-centric compositional imagination for visual abstract reasoning. In ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality, 2022.
[5] Dzmitry Bahdanau, Harm de Vries, Timothy J O'Donnell, Shikhar Murty, Philippe Beaudoin, Yoshua Bengio, and Aaron Courville. Closure: Assessing systematic generalization of clevr models. arXiv preprint arXiv:1912.05783, 2019.
[6] Dzmitry Bahdanau, Shikhar Murty, Michael Noukhovitch, Thien Huu Nguyen, Harm de Vries, and Aaron Courville. Systematic generalization: what is required and can it be learned? arXiv preprint arXiv:1811.12889, 2018.
[7] Jacob JW Bakermans, Joseph Warren, James CR Whittington, and Timothy EJ Behrens. Constructing future behaviour in the hippocampal formation through composition and replay. bioRxiv, pages 2023-04, 2023.
[8] Amir Bar, Yossi Gandelsman, Trevor Darrell, Amir Globerson, and Alexei A. Efros. Visual prompting via image inpainting. ArXiv, abs/2209.00647, 2022.
[9] Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, and Christian Wolf. Cophy: Counterfactual learning of physical dynamics. ArXiv, abs/1909.12000, 2019.
[10] David Barrett, Felix Hill, Adam Santoro, Ari Morcos, and Timothy Lillicrap. Measuring abstract reasoning in neural networks. In International conference on machine learning, pages 511-520. PMLR, 2018.
[11] Daniel Bear, Elias Wang, Damian Mrowca, Felix Binder, Hsiau-Yu Fish Tung, R. T. Pramod, Cameron Holdaway, Sirui Tao, Kevin A. Smith, Li Fei-Fei, Nancy G. Kanwisher, Joshua B. Tenenbaum, Daniel Yamins, and Judith E. Fan. Physion: Evaluating physical prediction from vision in humans and machines. ArXiv, abs/2106.08261, 2021.
[12] Timothy EJ Behrens, Timothy H Muller, James CR Whittington, Shirley Mark, Alon B Baram, Kimberly L Stachenfeld, and Zeb Kurth-Nelson. What is a cognitive map? organizing knowledge for flexible behavior. Neuron, 100(2):490-509, 2018.
[13] Yoshua Bengio, Aaron Courville, and Pascal Vincent. Representation learning: A review and new perspectives. IEEE transactions on pattern analysis and machine intelligence, 35(8):1798-1828, 2013.
[14] Yaniv Benny, Niv Pekar, and Lior Wolf. Scale-localized abstract reasoning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 12557-12565, 2021.
[15] Silvia Bernardi, Marcus K Benna, Mattia Rigotti, Jérôme Munuera, Stefano Fusi, and C Daniel Salzman. The geometry of abstraction in the hippocampus and prefrontal cortex. Cell, 183(4):954–967, 2020.
[16] Ben Bogin, Shivanshu Gupta, Matt Gardner, and Jonathan Berant. Covr: A test-bed for visually grounded compositional generalization with real images. arXiv preprint arXiv:2109.10613, 2021.
[17] Christopher P Burgess, Loic Matthew, Nicholas Watters, Rishabh Kabra, Irina Higgins, Matt Botvinick, and Alexander Lerchner. Monet: Unsupervised scene decomposition and representation. arXiv preprint arXiv:1901.11390, 2019.
[18] Mark Chen, Alec Radford, Jeff Wu, Heewoo Jun, Prafulla Dhariwal, David Luan, and Ilya Sutskever. Generative pretraining from pixels. In International Conference on Machine Learning, 2020.
[19] François Chollet. On the measure of intelligence. arXiv preprint arXiv:1911.01547, 2019.