Thomas L. Griffiths

Thomas L. Griffiths

Princeton University

H-index: 110

North America-United States

About Thomas L. Griffiths

Thomas L. Griffiths, With an exceptional h-index of 110 and a recent h-index of 78 (since 2020), a distinguished researcher at Princeton University, specializes in the field of Computational Models of Cognition, Cognitive Science, Machine Learning, Cognitive Psychology, Bayesian Statistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Reconciling categorization and memory via environmental statistics

Alignment with human representations supports robust few-shot learning

Preference-Conditioned Language-Guided Abstraction

Estimating subjective probability distributions

Recovering mental representations from large language models with markov chain monte carlo

Using Compositionality to Learn Many Categories from Few Examples

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

Analyzing the Roles of Language and Vision in Learning from Limited Data

Thomas L. Griffiths Information

University

Position

Professor of Psychology and Computer Science

Citations(all)

63364

Citations(since 2020)

28444

Cited By

46447

hIndex(all)

110

hIndex(since 2020)

78

i10Index(all)

352

i10Index(since 2020)

289

Email

University Profile Page

Princeton University

Google Scholar

View Google Scholar Profile

Thomas L. Griffiths Skills & Research Interests

Computational Models of Cognition

Cognitive Science

Machine Learning

Cognitive Psychology

Bayesian Statistics

Top articles of Thomas L. Griffiths

Title

Journal

Author(s)

Publication Date

Reconciling categorization and memory via environmental statistics

Psychonomic Bulletin & Review

Arjun Devraj

Thomas L Griffiths

Qiong Zhang

2024/2/16

Alignment with human representations supports robust few-shot learning

Advances in Neural Information Processing Systems

Ilia Sucholutsky

Tom Griffiths

2024/2/13

Preference-Conditioned Language-Guided Abstraction

Andi Peng

Andreea Bobu

Belinda Z Li

Theodore R Sumers

Ilia Sucholutsky

...

2024/3/11

Estimating subjective probability distributions

TL Griffiths

Adam N Sanborn

R Marjieh

T Langlois

J Xu

...

2024

Recovering mental representations from large language models with markov chain monte carlo

arXiv preprint arXiv:2401.16657

Jian-Qiao Zhu

Haijiang Yan

Thomas L Griffiths

2024/1/30

Using Compositionality to Learn Many Categories from Few Examples

Ilia Sucholutsky

Bonan Zhao

Thomas L Griffiths

2024/2/6

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

arXiv preprint arXiv:2402.07282

Ryan Liu

Theodore R Sumers

Ishita Dasgupta

Thomas L Griffiths

2024/2/11

Analyzing the Roles of Language and Vision in Learning from Limited Data

arXiv preprint arXiv:2403.19669

Allison Chen

Ilia Sucholutsky

Olga Russakovsky

Thomas L Griffiths

2024/2/15

The universal law of generalization holds for naturalistic stimuli.

Journal of Experimental Psychology: General

Raja Marjieh

Nori Jacoby

Joshua C Peterson

Thomas L Griffiths

2024/3

Capturing the growth of knowledge with nonparametric Bayesian models

J Austerwell

Adam N Sanborn

C Lucas

TL Griffiths

2024

Concept alignment

arXiv preprint arXiv:2401.08672

Sunayana Rane

Polyphony J Bruna

Ilia Sucholutsky

Christopher Kello

Thomas L Griffiths

2024/1/9

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

arXiv preprint arXiv:2402.04203

Declan Campbell

Sreejan Kumar

Tyler Giallanza

Thomas L Griffiths

Jonathan D Cohen

2024/2/6

A Rational Analysis of the Speech-to-Song Illusion

arXiv preprint arXiv:2402.06992

Raja Marjieh

Pol van Rijn

Ilia Sucholutsky

Harin Lee

Thomas L Griffiths

...

2024/2/10

Tree of thoughts: Deliberate problem solving with large language models

Neural Information Processing Systems (NeurIPS)

Shunyu Yao

Dian Yu

Jeffrey Zhao

Izhak Shafran

Thomas L Griffiths

...

2023/5/17

Characterizing the Large-Scale Structure of Grounded Semantic Networks

Raja Marjieh

Pol van Rijn

Ilia Sucholutsky

Harin Lee

Nori Jacoby

...

2024/4/2

Learning with language-guided state abstractions

arXiv preprint arXiv:2402.18759

Andi Peng

Ilia Sucholutsky

Belinda Z Li

Theodore R Sumers

Thomas L Griffiths

...

2024/2/28

Sampling as a bridge across levels of analysis

TL Griffiths

E Vul

Adam N Sanborn

Nick Chater

2024

Comparing human behavior to an optimal policy for innovation

Bonan Zhao

Natalia Vélez

Thomas L Griffiths

2024

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

arXiv preprint arXiv:2402.03618

Sreejan Kumar

Raja Marjieh

Byron Zhang

Declan Campbell

Michael Y Hu

...

2024/2/6

Distilling Symbolic Priors for Concept Learning into Neural Networks

arXiv preprint arXiv:2402.07035

Ioana Marinescu

R Thomas McCoy

Thomas L Griffiths

2024/2/10

See List of Professors in Thomas L. Griffiths University(Princeton University)

Co-Authors

H-index: 150
Jonathan D. Cohen

Jonathan D. Cohen

Princeton University

H-index: 137
Joshua B. Tenenbaum

Joshua B. Tenenbaum

Massachusetts Institute of Technology

H-index: 92
Alison GOPNIK

Alison GOPNIK

University of California, Berkeley

H-index: 76
Noah D. Goodman

Noah D. Goodman

Stanford University

H-index: 72
Fei Xu (徐绯)

Fei Xu (徐绯)

University of California, Berkeley

H-index: 60
Mark Steyvers

Mark Steyvers

University of California, Irvine

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