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Thomas L. Griffiths

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Embodied LLM Agents Learn to Cooperate in Organized Teams

Mar 19, 2024
Xudong Guo, Kaixuan Huang, Jiale Liu, Wenhui Fan, Natalia Vélez, Qingyun Wu, Huazheng Wang, Thomas L. Griffiths, Mengdi Wang

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Learning with Language-Guided State Abstractions

Mar 06, 2024
Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore R. Sumers, Thomas L. Griffiths, Jacob Andreas, Julie A. Shah

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Program-Based Strategy Induction for Reinforcement Learning

Feb 26, 2024
Carlos G. Correa, Thomas L. Griffiths, Nathaniel D. Daw

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How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?

Feb 13, 2024
Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths

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Distilling Symbolic Priors for Concept Learning into Neural Networks

Feb 10, 2024
Ioana Marinescu, R. Thomas McCoy, Thomas L. Griffiths

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A Rational Analysis of the Speech-to-Song Illusion

Feb 10, 2024
Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Harin Lee, Thomas L. Griffiths, Nori Jacoby

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Human-Like Geometric Abstraction in Large Pre-trained Neural Networks

Feb 06, 2024
Declan Campbell, Sreejan Kumar, Tyler Giallanza, Thomas L. Griffiths, Jonathan D. Cohen

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Measuring Implicit Bias in Explicitly Unbiased Large Language Models

Feb 06, 2024
Xuechunzi Bai, Angelina Wang, Ilia Sucholutsky, Thomas L. Griffiths

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Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction

Feb 06, 2024
Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden Lake, Thomas L. Griffiths

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