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All Topics CI Causal Induction CD Cognitive Development CEIL Cultural Evolution and Iterated Learning DMRL Decision Making and Reinforcement Learning E Education F Foundations IB Inductive Biases NBM Nonparametric Bayesian Models P Perception PR Probabilistic Reasoning RPM Rational Process Models S&C Similarity and Categorization SC Social Cognition SML Statistical Models of Language
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DMRL F Arumugam, D. , & Griffiths, T.L. (2025). On Temporal Credit Assignment and Data-Efficient Reinforcement Learning. Finding the Frame Workshop at RLC (pdf)
DMRL SML Arumugam, D. , & Griffiths, T. L. (2025). Toward efficient exploration by large language model agents. (preprint)
DMRL F Bastankhah, M. , Liu, G. , Arumugam, D. , Griffiths, T. L. , & Eysenbach, B. (2025). Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL. (preprint)
PR SML Geng, J. , Chen, H. , Arumugam, D. , & Griffiths, T. L. (2025). Are Large Language Models Reliable AI Scientists? Assessing Reverse-Engineering of Black-Box Systems. (preprint)
DMRL F Turner, C. R. , Arumugam, D. , Nelson, L. , & Griffiths, T. L. (2025). Trade-offs between tasks induced by capacity constraints bound the scope of intelligence. 47th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL SML Veselovsky, V. , Stroebl, B. , Bencomo, G. , Arumugam, D. , Schut, L. , Narayanan, A. , & Griffiths, T. L. (2025). Hindsight Merging: Diverse Data Generation with Language Models. Proceedings of the 41st Conference on Uncertainty in Artificial Intelligence. (pdf)
CEIL DMRL Zhao, B. , Mieczkowski, E. , Arumugam, D. , Velez, N. , & Griffiths, T. L. (2025). Discovering Hidden Laws in Innovation by Recombination. 47th Annual Meeting of the Cognitive Science Society. (pdf)
DMRL SML Zhu, J. Q. , Xie, H. , Arumugam, D. , Wilson, R. C. , & Griffiths, T. L. (2025). Using reinforcement learning to train large language models to explain human decisions. (preprint)