Thomas L. Griffiths
48 papers · 2006–2026 · 12 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 22 separate collaboration groups - the largest holds only 35% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Thomas L. Griffiths?
8 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Ilia Sucholutsky, Joseph L. Austerweil, Joshua T. Abbott
17 papers
· 2008–2025
· NeurIPS, ICML, ICLR
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Large Language Models Assume People are More Rational than We Really are
ICLR 2025
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
ICML 2025
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
ICML 2024
Learning Human-like Representations to Enable Learning Human Values
NeurIPS 2024
Learning with Language-Guided State Abstractions
ICLR 2024
Analyzing Diffusion as Serial Reproduction
ICML 2023
On the informativeness of supervision signals
UAI 2023
Words are all you need? Language as an approximation for human similarity judgments
ICLR 2023
Cognitive model priors for predicting human decisions
ICML 2019
Human Uncertainty Makes Classification More Robust
ICCV 2019
Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report
IJCAI 2017
Human memory search as a random walk in a semantic network
NeurIPS 2012
An ideal observer model for identifying the reference frame of objects
NeurIPS 2011
Testing a Bayesian Measure of Representativeness Using a Large Image Database
NeurIPS 2011
The Indian Buffet Process: An Introduction and Review
JMLR 2011
Learning invariant features using the Transformed Indian Buffet Process
NeurIPS 2010
Analyzing human feature learning as nonparametric Bayesian inference
NeurIPS 2008
14 papers whose co-authors appear nowhere else under this name
Language Models Trained to do Arithmetic Predict Human Risky and Intertemporal Choice
ICLR 2025
Gaussian Process Surrogate Models for Neural Networks
UAI 2023
A rational model of causal inference with continuous causes
NeurIPS 2011
Differential Use of Implicit Negative Evidence in Generative and Discriminative Language Learning
NeurIPS 2009
Neural Implementation of Hierarchical Bayesian Inference by Importance Sampling
NeurIPS 2009
Nonparametric Latent Feature Models for Link Prediction
NeurIPS 2009
A rational model of preference learning and choice prediction by children
NeurIPS 2008
How memory biases affect information transmission: A rational analysis of serial reproduction
NeurIPS 2008
Modeling human function learning with Gaussian processes
NeurIPS 2008
Modeling the effects of memory on human online sentence processing with particle filters
NeurIPS 2008
Markov Chain Monte Carlo with People
NeurIPS 2007
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments
NeurIPS 2006
Particle Filtering for Nonparametric Bayesian Matrix Factorization
NeurIPS 2006
Unsupervised Topic Modelling for Multi-Party Spoken Discourse
ACL 2006