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PR SML Bai, X. , Wang, A. , Sucholutsky, I. , & Griffiths, T. L. (2025). Explicitly unbiased large language models still form biased associations. Proceedings of the National Academy of Sciences, 122 (8), e2416228122. (pdf)
F Ku, A. , Campbell, D. , Bai, X. , Geng, J. , Liu, R. , Marjieh, R. , McCoy, R. T. , Nam, A. , Sucholutsky, I. , Veselovsky, V. , Zhang, L. , Zhu, J. Q. , & Griffiths, T. L. (2025). Using the tools of cognitive science to understand large language models at different levels of analysis. (preprint)
SC SML Liu, R. , Geng, J. , Peterson, J. C. , Sucholutsky, I. , & Griffiths, T. L. (2025). Large language models assume people are more rational than we really are. Proceedings of the 13th International Conference on Learning Representations (ICLR). (pdf)
PR SML Liu, R. , Geng, J. , Wu, A. J. , Sucholutsky, I. , Lombrozo, T. , & Griffiths, T. L. (2025). Mind your step (by step): Chain-of-thought can reduce performance on tasks where thinking makes humans worse. Proceedings of the 42nd International Conference on Machine Learning (ICML). (pdf)
S&C SML Marjieh, R. , Veselovsky, V. , Griffiths, T. L. , & Sucholutsky, I. (2025). What is a number, that a large language model may know it? (preprint)
F Sucholutsky, I. , Zhao, B. , Hwang, H. , Chen, A. , Russakovsky, O. , Griffiths, T. L. (2025). Learning a doubly-exponential number of concepts from few examples. (preprint)
F Ying, L. , Collins, K. M. , Wong, L. , Sucholutsky, I. , Liu, R. , Weller, A. , Shu, T. , Griffiths, T. L. , & Tenenbaum, J. B. (2025). On benchmarking human-like intelligence in machines. (preprint)
SC SML Bai, X. , Wang, A. , Sucholutsky, I. , & Griffiths, T. L. (2024). Measuring implicit bias in explicitly unbiased large language models. (preprint)
P Chen, A. , Sucholutsky, I. , Russakovsky, O. , & Griffiths, T. L. (2024). Analyzing the roles of language and vision in learning from limited data. 46th Annual Meeting of the Cognitive Science Society. (pdf)
F SC Collins, K. M. , Sucholutsky, I. , Bhatt, U. , Chandra, K. , Wong, L. , Lee, M. , Zhang, C. E. , Zhi-Xuan, T. , Ho, M. , Mansinghka, V. , Weller, A. , Tenenbaum, J. B. , & Griffiths, T. L. (2024). Building machines that learn and think with people. Nature Human Behaviour, 8 (10), 1851-1863. (pdf)
F PR Malaviya, M. , Sucholutsky, I. , & Griffiths, T. L. (2024). Pushing the limits of learning from limited data. Proceedings of the AAAI Symposium Series, 3 (1), 559-561. (pdf)
P Marjieh, R. , van Rijn, P. , Sucholutsky, I. , Lee, H. , Griffiths, T. L. , & Jacoby, N. (2024). A rational analysis of the speech-to-song illusion. 46th Annual Meeting of the Cognitive Science Society. (pdf)
P SML Marjieh, R. , van Rijn, P. , Sucholutsky, I. , Lee, H. , Jacoby, N. , & Griffiths, T. L. (2024). Characterizing the large-scale structure of grounded semantic networks. (preprint)
S&C SML Marjieh, R. , Sucholutsky, I. , van Rijn, P. , Jacoby, N. , & Griffiths, T. L. (2024). Large language models predict human sensory judgments across six modalities. Scientific Reports, 14 (1), 21445.(pdf)
P Niedermann, J. P. , Sucholutsky, I. , Marjieh, R. , Çelen, E. , Griffiths, T. , Jacoby, N. , & van Rijn, P. (2024) Studying the effect of globalization on color perception using multilingual online recruitment and large language models. 46th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL SC Oktar, K. , Sucholutsky, I. , Lombrozo, T. , & Griffiths, T. L. (2024). Dimensions of disagreement: Unpacking divergence and misalignment in cognitive science and artificial intelligence. Decision, 11 (4), 511–522. (pdf)
DMRL SML Peng, A. , Sucholutsky, I. , Li, B. Z. , Sumers, T. R. , Griffiths, T. L. , Andreas, J. , & Shah, J. A. (2024). Learning with language-guided state abstractions. Proceedings of the 12th International Conference on Learning Representations (ICLR). (pdf)
DMRL SML Peng, A. , Bobu, A. , Li, B. Z. , Sumers, T. R. , Sucholutsky, I. , Kumar, N. , & Griffiths, T. L. (2024). Preference-conditioned language-guided abstraction. Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction. (pdf)
IB S&C Rane, S. , Ho, M. , Sucholutsky, I. , & Griffiths, T. L. (2024). Concept alignment as a prerequisite for value alignment. 46th Annual Meeting of the Cognitive Science Society. (pdf)
S&C SC Sucholutsky, I. , Collins, K. M. , Malaviya, M. , Jacoby, N. , Liu, W. , Sumers, T. R. , Korakakis, M. , Bhatt, U. , Ho, M. , Tenenbaum, J. B. , Love, B. , Pardos, Z. A. , Weller, A. , & Griffiths, T. L. (2024). Representational alignment supports effective machine teaching. (preprint)
IB Sucholutsky, I. , & Griffiths, T. L. (2024). Why should we care if machines learn human-like representations? AAAI-24 Spring Symposium on Human-Like Learning . (pdf)
S&C Sucholutsky, I. , Zhao, B. , & Griffiths, T. L. (2024). Using compositionality to learn many categories from few examples. 46th Annual Meeting of the Cognitive Science Society. (pdf)
IB S&C Wynn, A. H. , Sucholutsky, I. , Griffiths, T. L. (2024). Learning human-like representations to enable learning human values. Advances in Neural Information Processing Systems 38 . (pdf)
S&C Marjieh, R. , Van Rijn, P. , Sucholutsky, I. , Sumers, T. , Lee, H. , Griffiths, T. L. , & Jacoby, N. (2023) Words are all you need? Language as an approximation for human similarity judgments. Proceedings of the 11th International Conference on Learning Representations (ICLR). (preprint)
P PR Marjieh, R. , Sucholutsky, I. , Langlois, T. A. , Jacoby, N. , & Griffiths, T. L. (2023) Analyzing diffusion as serial reproduction. Proceedings of the 40th International Conference on Machine Learning (ICML), 202 24005-24019. (preprint)
P SML Marjieh, R. , Sucholutsky, I. , van Rijn, P. , Jacoby, N. , & Griffiths, T. L. (2023). What language reveals about perception: Distilling psychophysical knowledge from large language models. 45th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL IB Rane, S. , Ho, M. , Sucholutsky, I. , & Griffiths, T. L. (2023). Concept alignment as a prerequisite for value alignment. AAAI 2024 Bridge on Collaborative AI and Modeling of Humans. (pdf)
S&C Sucholutsky, I. , Battleday, R. , Collins, K. , Marjieh, R. , Peterson, J. C. , Singh, P. , Bhatt, U. , Jacoby, N. , Weller, A. , & Griffiths, T. L. (2023). On the informativeness of supervision signals. Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence. (pdf)
IB P Sucholutsky, I. , & Griffiths, T. L. (2023). Alignment with human representations supports robust few-shot learning. Advances in Neural Information Processing Systems 37. (pdf)
F Sucholutsky, I. , Muttenthaler, L. , Weller, A. , Peng, A. , Bobu, A. , Kim, B. , Love, B. C. , Grant, E. , Achterberg, J. , Tenenbaum, J. B. , Collins, K. M. , Hermann, K. L. , Oktar, K. , Greff, K. , Hebart, M. N. , Jacoby, N. , Marjieh, R. , Geirhos, R. , Chen, S. , Kornblith, S. , Rane, S. , Konkle, T. , O'Connell, T. P. , Unterthiner, T. , Lampinen, A. K. , Müller, K.-R. , Toneva, M. , & Griffiths, T. L. (2023). Getting aligned on representational alignment. (preprint)
S&C Malaviya, M. , Sucholutsky, I. , Oktar, K. , & Griffiths, T. L. (2022). Can Humans Do Less-Than-One-Shot Learning? Proceedings of the 44th Annual Conference of the Cognitive Science Society. (pdf)
S&C SML Marjieh, R. , Sucholutsky, I. , Sumers, T. R. , Jacoby, N. , & Griffiths, T. L. (2022). Predicting Human Similarity Judgments Using Large Language Models. Proceedings of the 44th Annual Conference of the Cognitive Science Society. (pdf)