Publications: 
Computational Principles of Intelligence

Hussain, Z.; Binz, M.; Mata, R.; Wulff, D.: A tutorial on open-source large language models for behavioral science. Behavior Research Methods 56 (8), pp. 8214 - 8237 (2024)

Hedrich, N.; Schulz, E.; Hall-McMaster, S.; Schuck, N.: An inductive bias for slowly changing features in human reinforcement learning. PLOS Computational Biology 20 (11), e1012568 (2024)

Binz, M.; Dasgupta, I.; Jagadish, A.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-learning: Data, architecture, and both. Behavioral and Brain Sciences 47, e170 (2024)

Thalmann, M.; Schäfer, T.; Theves, S.; Doeller, C.; Schulz, E.: Task Imprinting: Another Mechanism of Representational Change? Cognitive Neuroscience 152, 101670 (2024)

Allen, K.; Brändle, F.; Botvinick, M.; Fan, J.; Gershman, S.; Gopnik, A.; Griffiths, T.; Hartshorne, J.; Hauser, T.; Ho, M. et al.; de Leeuw, J.; Ma, W.; Murayama, K.; Nelson, J.; van Opheusden, B.; Poundsy, T.; Rafner, J.; Rahwan, I.; Rutledge, R.; Sherson, J.; Şimşek, Ö.; Spiers, H.; Summerfield, C.; Thalmann, M.; Vélez, N.; Watrous, A.; Tenenbaum, J.; Schulz, E.: Using Games to Understand the Mind. Nature Human Behaviour 8 (6), pp. 1035 - 1043 (2024)

Nath, S.; Brändle, F.; Schulz, E.; Dayan, P.; Brielmann, A.: Relating Objective Complexity, Subjective Complexity and Beauty in Binary Pixel Patterns. Psychology of Aesthetics, Creativity, and the Arts Epub ahead (2024)

Binz, M.; Dasgupta, I.; Jagadish, A.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-Learned Models of Cognition. Behavioral and Brain Sciences 47, e147 (2024)

Ruggeri, A.; Stanciu, O.; Pelz, M.; Gopnik, A.; Schulz, E.: Preschoolers search longer when there is more information to be gained. Developmental Science 27 (1), e13411 (2024)

Demircan, C.; Saanum, T.; Pettini, L.; Binz, M.; Baczkowski, B.; Doeller, C.; Garvert, M.; Schulz, E.: Evaluating alignment between humans and neural network representations in image-based learning tasks. In: Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024). Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024), Vancouver, Canada, December 11, 2024 - December 15, 2024. (2024)

Brändle, F.; Kessler, S.; Ruggeri, A.; Schulz, E.: Uncertainty-driven little alchemists: Differences in exploration strategies between adults and children in an online game. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024). 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Wu, S.; Thalmann, M.; Schulz, E.: Learning abstractions from discrete sequences. In: 46th Annual Conference of the Cognitive Science Society (CogSci 2024). 46th Annual Conference of the Cognitive Science Society (CogSci 2024), Rotterdam, The Netherlands, July 24, 2024 - July 27, 2024. (2024)

Binz, M.; Schulz, E.: Turning large language models into cognitive models. In: Twelfth International Conference on Learning Representations (ICLR 2024). Twelfth International Conference on Learning Representations (ICLR 2024), Wien, Austria, May 07, 2024 - May 11, 2024. (2024)

Coda-Forno, J.; Binz, M.; Akata, Z.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-in-context learning in large language models. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2844, pp. 65189 - 65201 (Eds. Ho, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2710, pp. 61985 - 62005 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Salewski, L.; Alaniz, S.; Rio-Torto, I.; Schulz, E.; Akata, Z.: In-Context Impersonation Reveals Large Language Models’ Strengths and Biases. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 3152, pp. 72044 - 72057 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Coda-Forno, J.; Binz, M.; Wang, J.; Schulz, E.: CogBench: a large language model walks into a psychology lab. In: Proceedings of Machine Learning Research: PLMR, Vol. 235, pp. 9076 - 9108. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 2024. (2024)

Jagadish, A.; Coda-Forno, J.; Thalmann, M.; Schulz, E.; Binz, M.: Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks. In: Proceedings of Machine Learning Research: PLMR, Vol. 235, pp. 21121 - 21147. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 2024. (2024)

Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: In-Context Learning Agents Are Asymmetric Belief Updaters. In: Proceedings of Machine Learning Research: PLMR, Vol. 235, pp. 43928 - 43946. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 2024. (2024)

Wu, S.; Yoerueten, M.; Wichmann, F.; Schulz, E.: Normalized Cuts Characterize Visual Recognition Difficulty of Amorphous Image Sub-parts. Computational and Systems Neuroscience Meeting (COSYNE 2024), Lisboa, Portugal (2024)

Binz, M.; Akata, E.; Bethge, M.; Brändle, F.; Callaway, F.; Coda-Forno, J.; Dayan, P.; Demircan, C.; Eckstein, M.; Éltetö, N. et al.; Griffiths, T.; Haridi, S.; Jagadish, A.; Ji-An; Kipnis, A.; Kumar, S.; Ludwig, T.; Mathony, M.; Mattar, M.; Modirshanechi, A.; Nath, S.; Peterson, J.; Rmus, M.; Russek, E.; Saanum, T.; Scharfenberg, N.; Schubert, J.; Schulze Buschoff, L.; Singhi, N.; Sui, X.; Thalmann, M.; Theis, F.; Truong, V.; Udandarao, V.; Voudouris, K.; Wilson, R.; Witte, K.; Wu, S.; Wulff, D.; Xiong, H.; Schulz, E.: Centaur: a foundation model of human cognition. (submitted)