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Thomas L. Griffiths

Distinguishing rule- and exemplar-based generalization in learning systems


Oct 08, 2021
Ishita Dasgupta, Erin Grant, Thomas L. Griffiths

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* 9 pages 
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Cognitive science as a source of forward and inverse models of human decisions for robotics and control


Sep 01, 2021
Mark K. Ho, Thomas L. Griffiths

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* Invited submission for Annual Review of Control, Robotics, and Autonomous Systems 
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Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment


Jul 21, 2021
Michael Chang, Sidhant Kaushik, Sergey Levine, Thomas L. Griffiths

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* Long Presentation at the Thirty-eighth International Conference on Machine Learning (ICML) 2021. 21 pages, 11 figures. v2: updated acknowledgments. v3: clarified that the internal function nodes of the credit assignment mechanism are not considered O(1) 
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Passive attention in artificial neural networks predicts human visual selectivity


Jul 14, 2021
Thomas A. Langlois, H. Charles Zhao, Erin Grant, Ishita Dasgupta, Thomas L. Griffiths, Nori Jacoby

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Extending rational models of communication from beliefs to actions


May 25, 2021
Theodore R. Sumers, Robert D. Hawkins, Mark K. Ho, Thomas L. Griffiths

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* 7 pages, 4 figures. Proceedings for the 43rd Annual Meeting of the Cognitive Science Society 
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Are Convolutional Neural Networks or Transformers more like human vision?


May 15, 2021
Shikhar Tuli, Ishita Dasgupta, Erin Grant, Thomas L. Griffiths

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* Accepted at CogSci 2021 
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Control of mental representations in human planning


May 14, 2021
Mark K. Ho, David Abel, Carlos G. Correa, Michael L. Littman, Jonathan D. Cohen, Thomas L. Griffiths

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Shades of confusion: Lexical uncertainty modulates ad hoc coordination in an interactive communication task


May 13, 2021
Sonia K. Murthy, Robert D. Hawkins, Thomas L. Griffiths

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* under review 
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From partners to populations: A hierarchical Bayesian account of coordination and convention


Apr 12, 2021
Robert D. Hawkins, Michael Franke, Michael C. Frank, Kenny Smith, Thomas L. Griffiths, Noah D. Goodman

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* Draft version, 4/12/2021. This paper has not been peer reviewed. Please do not copy or cite without author's permission 
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Evaluating Models of Robust Word Recognition with Serial Reproduction


Jan 24, 2021
Stephan C. Meylan, Sathvik Nair, Thomas L. Griffiths

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* Cognition Volume 210, May 2021, 104553 
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Show or Tell? Demonstration is More Robust to Changes in Shared Perception than Explanation


Dec 16, 2020
Theodore R. Sumers, Mark K. Ho, Thomas L. Griffiths

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* 7 pages, 4 figures. Proceedings for the 42nd Annual Meeting of the Cognitive Science Society 
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Competition in Cross-situational Word Learning: A Computational Study


Dec 06, 2020
Aida Nematzadeh, Zahra Shekarchi, Thomas L. Griffiths, Suzanne Stevenson

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* 38 pages, 4 figures, 2 tables 
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Investigating representations of verb bias in neural language models


Oct 15, 2020
Robert D. Hawkins, Takateru Yamakoshi, Thomas L. Griffiths, Adele E. Goldberg

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* Accepted to EMNLP 
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Meta-Learning of Compositional Task Distributions in Humans and Machines


Oct 05, 2020
Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths

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Learning Rewards from Linguistic Feedback


Sep 30, 2020
Theodore R. Sumers, Mark K. Ho, Robert D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths

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* 9 pages, 4 figures 
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Understanding Human Intelligence through Human Limitations


Sep 29, 2020
Thomas L. Griffiths

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* In press at Trends in Cognitive Sciences 
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Resource-rational Task Decomposition to Minimize Planning Costs


Jul 27, 2020
Carlos G. Correa, Mark K. Ho, Fred Callaway, Thomas L. Griffiths

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* The first two authors contributed equally. To appear in Proceedings of the 42nd Annual Conference of the Cognitive Science Society (CogSci 2020) 
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End-to-end Deep Prototype and Exemplar Models for Predicting Human Behavior


Jul 17, 2020
Pulkit Singh, Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths

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* 7 pages, 4 figures, 2 tables. Accepted as a paper to the 42nd Annual Meeting of the Cognitive Science Society (CogSci 2020) 
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Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions


Jul 05, 2020
Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine

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* 17 pages, 12 figures, accepted to the International Conference on Machine Learning (ICML) 2020 
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Universal linguistic inductive biases via meta-learning


Jun 29, 2020
R. Thomas McCoy, Erin Grant, Paul Smolensky, Thomas L. Griffiths, Tal Linzen

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* To appear in the Proceedings of the 42nd Annual Conference of the Cognitive Science Society 
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Analogy as Nonparametric Bayesian Inference over Relational Systems


Jun 07, 2020
Ruairidh M. Battleday, Thomas L. Griffiths

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* In Proceedings for the Annual Meeting of the Cognitive Science Society 2020 (CogSci 2020) 
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Extracting low-dimensional psychological representations from convolutional neural networks


May 29, 2020
Aditi Jha, Joshua Peterson, Thomas L. Griffiths

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* Accepted to CogSci 2020 
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The Efficiency of Human Cognition Reflects Planned Information Processing


Feb 13, 2020
Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths

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* 13 pg (incl. supplemental materials); included in Proceedings of the 34th AAAI Conference on Artificial Intelligence 
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Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks


Feb 04, 2020
Robert D. Hawkins, Noah D. Goodman, Adele E. Goldberg, Thomas L. Griffiths

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Scaling up Psychology via Scientific Regret Minimization: A Case Study in Moral Decision-Making


Oct 16, 2019
Mayank Agrawal, Joshua C. Peterson, Thomas L. Griffiths

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On the Utility of Learning about Humans for Human-AI Coordination


Oct 13, 2019
Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca Dragan

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* Published at NeurIPS 2019 
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Human uncertainty makes classification more robust


Aug 19, 2019
Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, Olga Russakovsky

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* In Proceedings of the 2019 IEEE International Conference on Computer Vision (ICCV) 
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