Thomas L. Griffiths
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
107
Venues
16
Active years
2004–2026
Best venue rank
A*
Where they publish
Papers
107 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation. | Kaiqu Liang, Haimin Hu, Ryan Liu, Thomas L. Griffiths, Jaime Fernndez Fisac |
| 2026 | ACL | Localized Cultural Knowledge is Conserved and Controllable in Large Language Models. | Veniamin Veselovsky, Berke Argin, Benedikt Stroebl, Chris Wendler, Robert West, James Evans, Thomas L. Griffiths, Arvind Narayanan |
| 2025 | EMNLP | Evaluating distillation methods for data-efficient syntax learning. | Takateru Yamakoshi, Thomas L. Griffiths, R. Thomas McCoy, Robert D. Hawkins |
| 2025 | ICLR | Large Language Models Assume People are More Rational than We Really are. | Ryan Liu, Jiayi Geng, Joshua C. Peterson, Ilia Sucholutsky, Thomas L. Griffiths |
| 2025 | ICLR | Language Models Trained to do Arithmetic Predict Human Risky and Intertemporal Choice. | Jian-Qiao Zhu, Haijiang Yan, Thomas L. Griffiths |
| 2025 | ICML | Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse. | Ryan Liu, Jiayi Geng, Addison J. Wu, Ilia Sucholutsky, Tania Lombrozo, Thomas L. Griffiths |
| 2025 | ICML | Conformal Prediction as Bayesian Quadrature. | Jake C. Snell, Thomas L. Griffiths |
| 2025 | UAI | Hindsight Merging: Diverse Data Generation with Language Models. | Veniamin Veselovsky, Benedikt Stroebl, Gianluca M. Bencomo, Dilip Arumugam, Lisa Schut, Arvind Narayanan, Thomas L. Griffiths |
| 2024 | EMNLP | Deciphering the Factors Influencing the Efficacy of Chain-of-Thought: Probability, Memorization, and Noisy Reasoning. | Akshara Prabhakar, Thomas L. Griffiths, R. Thomas McCoy |
| 2024 | HRI | Preference-Conditioned Language-Guided Abstraction. | Andi Peng, Andreea Bobu, Belinda Z. Li, Theodore R. Sumers, Ilia Sucholutsky, Nishanth Kumar, Thomas L. Griffiths, Julie A. Shah |
| 2024 | ICLR | Implicit Maximum a Posteriori Filtering via Adaptive Optimization. | Gianluca M. Bencomo, Jake Snell, Thomas L. Griffiths |
| 2024 | ICLR | Learning with Language-Guided State Abstractions. | Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore R. Sumers, Thomas L. Griffiths, Jacob Andreas, Julie Shah |
| 2024 | ICML | How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? | Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths |
| 2024 | NAACL | MacGyver: Are Large Language Models Creative Problem Solvers? | Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman |
| 2023 | ICLR | Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. | Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang |
| 2023 | ICLR | Words are all you need? Language as an approximation for human similarity judgments. | Raja Marjieh, Pol van Rijn, Ilia Sucholutsky, Theodore R. Sumers, Harin Lee, Thomas L. Griffiths, Nori Jacoby |
| 2023 | ICML | Analyzing Diffusion as Serial Reproduction. | Raja Marjieh, Ilia Sucholutsky, Thomas A. Langlois, Nori Jacoby, Thomas L. Griffiths |
| 2023 | UAI | Gaussian Process Surrogate Models for Neural Networks. | Michael Y. Li, Erin Grant, Thomas L. Griffiths |
| 2023 | UAI | On the informativeness of supervision signals. | Ilia Sucholutsky, Ruairidh M. Battleday, Katherine M. Collins, Raja Marjieh, Joshua C. Peterson, Pulkit Singh, Umang Bhatt, Nori Jacoby, Adrian Weller, Thomas L. Griffiths |
| 2022 | ACL | Probing BERT's priors with serial reproduction chains. | Takateru Yamakoshi, Thomas L. Griffiths, Robert D. Hawkins |
| 2021 | AAAI | Learning Rewards From Linguistic Feedback. | Theodore R. Sumers, Mark K. Ho, Robert X. D. Hawkins, Karthik Narasimhan, Thomas L. Griffiths |
| 2021 | ICLR | Meta-Learning of Structured Task Distributions in Humans and Machines. | Sreejan Kumar, Ishita Dasgupta, Jonathan D. Cohen, Nathaniel D. Daw, Thomas L. Griffiths |
| 2020 | AAAI | People Do Not Just Plan, They Plan to Plan. | Mark K. Ho, David Abel, Jonathan D. Cohen, Michael L. Littman, Thomas L. Griffiths |
| 2020 | EMNLP | Investigating representations of verb bias in neural language models. | Robert X. D. Hawkins, Takateru Yamakoshi, Thomas L. Griffiths, Adele E. Goldberg |
| 2019 | ICCV | Human Uncertainty Makes Classification More Robust. | Joshua C. Peterson, Ruairidh M. Battleday, Thomas L. Griffiths, Olga Russakovsky |
| 2019 | ICLR | Automatically Composing Representation Transformations as a Means for Generalization. | Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths |
| 2019 | ICML | Cognitive model priors for predicting human decisions. | David D. Bourgin, Joshua C. Peterson, Daniel Reichman, Stuart J. Russell, Thomas L. Griffiths |
| 2018 | EMNLP | Exploiting Attention to Reveal Shortcomings in Memory Models. | Kaylee Burns, Aida Nematzadeh, Erin Grant, Alison Gopnik, Thomas L. Griffiths |
| 2018 | EMNLP | Evaluating Theory of Mind in Question Answering. | Aida Nematzadeh, Kaylee Burns, Erin Grant, Alison Gopnik, Thomas L. Griffiths |
| 2018 | ICLR | Investigating Human Priors for Playing Video Games. | Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Thomas L. Griffiths |
| 2018 | ICLR | Recasting Gradient-Based Meta-Learning as Hierarchical Bayes. | Erin Grant, Chelsea Finn, Sergey Levine, Trevor Darrell, Thomas L. Griffiths |
| 2018 | UAI | Learning to select computations. | Frederick Callaway, Sayan Gul, Paul M. Krueger, Thomas L. Griffiths, Falk Lieder |
| 2017 | AAAI | When Does Bounded-Optimal Metareasoning Favor Few Cognitive Systems? | Smitha Milli, Falk Lieder, Thomas L. Griffiths |
| 2017 | CogSci | Empirical tests of large-scale collaborative recall. | Monica A. Gates, Jordan W. Suchow, Thomas L. Griffiths |
| 2017 | CogSci | How Can Memory-Augmented Neural Networks Pass a False-Belief Task? | Erin Grant, Aida Nematzadeh, Thomas L. Griffiths |
| 2017 | CogSci | Uncovering visual priors in spatial memory using serial reproduction. | Thomas A. Langlois, Nori Jacoby, Jordan W. Suchow, Thomas L. Griffiths |
| 2017 | CogSci | Evaluating Vector-Space Models of Word Representation, or, The Unreasonable Effectiveness of Counting Words Near Other Words. | Aida Nematzadeh, Stephan C. Meylan, Thomas L. Griffiths |
| 2017 | CogSci | Evidence for the size principle in semantic and perceptual domains. | Joshua C. Peterson, Thomas L. Griffiths |
| 2017 | IJCAI | Adapting Deep Network Features to Capture Psychological Representations: An Abridged Report. | Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths |
| 2017 | ISRR | Pragmatic-Pedagogic Value Alignment. | Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, Anca D. Dragan |
| 2016 | CogSci | The Sapir-Whorf Hypothesis and Probabilistic Inference: Evidence from the Domain of Color. | Emily Cibelli, Yang Xu, Joseph L. Austerweil, Thomas L. Griffiths, Terry Regier |
| 2016 | CogSci | Adapting Deep Network Features to Capture Psychological Representations. | Joshua C. Peterson, Joshua T. Abbott, Thomas L. Griffiths |
| 2016 | CogSci | Wallace: Automating Cultural Evolution Experiments Through Crowdsourcing. | Jordan W. Suchow, Thomas J. H. Morgan, Jessica B. Hamrick, Michael D. Pacer, Stephan C. Meylan, Thomas L. Griffiths |
| 2016 | CogSci | Design from Zeroth Principles. | Jordan W. Suchow, Michael D. Pacer, Thomas L. Griffiths |
| 2016 | EDM | Using Inverse Planning for Personalized Feedback. | Anna N. Rafferty, Rachel Jansen, Thomas L. Griffiths |
| 2016 | WAFR | Generating Plans that Predict Themselves. | Jaime F. Fisac, Chang Liu, Jessica B. Hamrick, Shankar Sastry, J. Karl Hedrick, Thomas L. Griffiths, Anca D. Dragan |
| 2015 | AIED | Interpreting Freeform Equation Solving. | Anna N. Rafferty, Thomas L. Griffiths |
| 2015 | CogSci | Think again? The amount of mental simulation tracks uncertainty in the outcome. | Jessica B. Hamrick, Kevin A. Smith, Thomas L. Griffiths, Ed Vul |
| 2015 | CogSci | Can children balance the size of a majority with the quality of their information? | Jane C. Hu, Andrew Whalen, Daphna Buchsbaum, Thomas L. Griffiths, Fei Xu |
| 2015 | CogSci | When to use which heuristic: A rational solution to the strategy selection problem. | Falk Lieder, Thomas L. Griffiths |
| 2015 | CogSci | Children and adults differ in their strategies for social learning. | Falk Lieder, Zi Lin Sim, Jane C. Hu, Thomas L. Griffiths, Fei Xu |
| 2015 | CogSci | Generative and Discriminative Models in Cognitive Science. | Bradley C. Love, Michael Ramscar, Thomas L. Griffiths, Matt Jones |
| 2015 | CogSci | A Bayesian Framework for Learning Words From Multiword Utterances. | Stephan C. Meylan, Thomas L. Griffiths |
| 2015 | CogSci | What the Baldwin Effect affects. | Thomas J. H. Morgan, Thomas L. Griffiths |
| 2015 | CogSci | Upsetting the contingency table: Causal induction over sequences of point events. | Michael Pacer, Thomas L. Griffiths |
| 2015 | CogSci | Children search for information as efficiently as adults, but seek additional confirmatory evidence. | Azzurra Ruggeri, Tania Lombrozo, Thomas L. Griffiths, Fei Xu |
| 2014 | CogSci | Is Holism A Problem For Inductive Inference? A Computational Analysis. | Maxwell A. Bertolero, Thomas L. Griffiths |
| 2014 | CogSci | Empirical Evidence for Markov Chain Monte Carlo in Memory Search. | David Bourgin, Joshua T. Abbott, Thomas L. Griffiths, Kevin A. Smith, Ed Vul |
| 2014 | CogSci | What to simulate? Inferring the right direction for mental rotation. | Jessica B. Hamrick, Thomas L. Griffiths |
| 2014 | CogSci | The high availability of extreme events serves resource-rational decision-making. | Falk Lieder, Ming Hsu, Thomas L. Griffiths |
| 2014 | CogSci | Moot Point Process Models. | Bradley C. Love, Jana Jarecki, Jerome R. Busemeyer, Niels A. Taatgen, Thomas L. Griffiths, Mirjam Jenny |
| 2014 | CogSci | The Telephone Game: Exploring Inductive Biases In Naturalistic Language Use. | Stephan C. Meylan, Brett Goldstein, Anna N. Rafferty, Thomas L. Griffiths |
| 2014 | CogSci | A Bounded Rationality Account of Wishful Thinking. | Rebecca Neumann, Anna N. Rafferty, Thomas L. Griffiths |
| 2014 | CogSci | Caching Algorithms and Rational Models of Memory. | Avi Press, Michael Pacer, Thomas L. Griffiths, Brian R. Christian |
| 2014 | CogSci | Cultural evolution with sparse testimony: when does the cultural ratchet slip? | Andrew Whalen, Luke Maurits, Michael Pacer, Thomas L. Griffiths |
| 2014 | EDM | Diagnosing Algebra Understanding via Bayesian Inverse Planning. | Anna N. Rafferty, Thomas L. Griffiths |
| 2013 | CogSci | Approximating Bayesian inference with a sparse distributed memory system. | Joshua T. Abbott, Jessica B. Hamrick, Thomas L. Griffiths |
| 2013 | CogSci | Inferring mass in complex physical scenes via probabilistic simulation. | Jessica B. Hamrick, Peter W. Battaglia, Thomas L. Griffiths, Joshua B. Tenenbaum |
| 2013 | CogSci | When does the majority rule? Preschoolers' trust in majority informants varies by task domain. | Jane C. Hu, Daphna Buchsbaum, Thomas L. Griffiths, Fei Xu |
| 2013 | CogSci | How do you know that? Sensitivity to statistical dependency in social learning. | Andrew Whalen, Daphna Buchsbaum, Thomas L. Griffiths |
| 2013 | UAI | Evaluating computational models of explanation using human judgments. | Michael Pacer, Joseph Jay Williams, Xi Chen, Tania Lombrozo, Thomas L. Griffiths |
| 2012 | CogSci | Constructing a hypothesis space from the Web for large-scale Bayesian word learning. | Joshua T. Abbott, Joseph L. Austerweil, Thomas L. Griffiths |
| 2012 | CogSci | Predicting focal colors with a rational model of representativeness. | Joshua T. Abbott, Terry Regier, Thomas L. Griffiths |
| 2012 | CogSci | Look-Ahead Monte Carlo with People. | Charles Blundell, Adam Sanborn, Thomas L. Griffiths |
| 2012 | CogSci | Do I know that you know what you know? Modeling testimony in causal inference. | Daphna Buchsbaum, Sophie Bridgers, Andrew Whalen, Elizabeth Seiver, Thomas L. Griffiths, Alison Gopnik |
| 2012 | CogSci | Thirty years of Marr's Vision: Levels of Analysis in Cognitive Science. | Chris Eliasmith, Thomas L. Griffiths, Valerie Gray Hardcastle, Bradley C. Love, William Bechtel, Richard P. Cooper, David Peebles |
| 2012 | CogSci | Comparing the inductive biases of simple neural networks and Bayesian models. | Thomas L. Griffiths, Joseph L. Austerweil, Vincent G. Berthiaume |
| 2012 | CogSci | Identifying representations of categories of discrete items using Markov chain Monte Carlo with People. | Anne S. Hsu, Jay B. Martin, Adam N. Sanborn, Thomas L. Griffiths |
| 2012 | CogSci | A Bayesian Model of Rule Induction in Raven's Progressive Matrices. | Daniel R. Little, Stephan Lewandowsky, Thomas L. Griffiths |
| 2012 | CogSci | Connecting input filtering and selection in language evolution. | Luke Maurits, Thomas L. Griffiths |
| 2012 | CogSci | Elements of a rational framework for continuous-time causal induction. | Michael Pacer, Thomas L. Griffiths |
| 2012 | CogSci | Optimally Designing Games for Cognitive Science Research. | Anna N. Rafferty, Matei Zaharia, Thomas L. Griffiths |
| 2012 | CogSci | Determining people's expectations about the form of causal relationships. | Saiwing Yeung, Christopher G. Lucas, Thomas L. Griffiths |
| 2012 | EDM | Inferring learners' knowledge from observed actions. | Anna N. Rafferty, Michelle M. LaMar, Thomas L. Griffiths |
| 2011 | AAAI | A Nonparametric Bayesian Model of Multi-Level Category Learning. | Kevin Robert Canini, Thomas L. Griffiths |
| 2011 | AIED | Faster Teaching by POMDP Planning. | Anna N. Rafferty, Emma Brunskill, Thomas L. Griffiths, Patrick Shafto |
| 2011 | CogSci | Exploring the influence of particle filter parameters on order effects in causal learning. | Joshua T. Abbott, Thomas L. Griffiths |
| 2011 | CogSci | Grow your own representations: Computational constructivism. | Joseph L. Austerweil, Thomas L. Griffiths, Todd M. Gureckis, Robert L. Goldstone, Kevin Robert Canini, Matt Jones |
| 2011 | CogSci | A Simple Sequential Algorithm for Approximating Bayesian Inference. | Elizabeth Bonawitz, Stephanie Denison, Annie Chen, Alison Gopnik, Thomas L. Griffiths |
| 2011 | CogSci | Segmenting and Recognizing Human Action using Low-level Video Features. | Daphna Buchsbaum, Kevin Robert Canini, Thomas L. Griffiths |
| 2011 | CogSci | Discovering Inductive Biases in Categorization through Iterated Learning. | Kevin Robert Canini, Thomas L. Griffiths, Wolf Vanpaemel, Michael L. Kalish |
| 2011 | CogSci | Young Toddlers' Understanding of Graded Preferences. | Jane C. Hu, Christopher G. Lucas, Thomas L. Griffiths, Fei Xu |
| 2011 | CogSci | From preferences to choices and back again: evidence for human inconsistency and its implications. | Christopher G. Lucas, Charles Kemp, Thomas L. Griffiths |
| 2011 | CogSci | A Bayesian model of navigation in squirrels. | Anna Waisman, Christopher G. Lucas, Thomas L. Griffiths, Lucia Jacobs |
| 2011 | CogSci | Estimating human priors on causal strength. | Saiwing Yeung, Thomas L. Griffiths |
| 2010 | ICML | Modeling Transfer Learning in Human Categorization with the Hierarchical Dirichlet Process. | Kevin Robert Canini, Mikhail M. Shashkov, Thomas L. Griffiths |
| 2009 | Interspeech | Connecting human and machine learning via probabilistic models of cognition. | Thomas L. Griffiths |
| 2009 | NAACL | Improved Reconstruction of Protolanguage Word Forms. | Alexandre Bouchard-Ct, Thomas L. Griffiths, Dan Klein |
| 2008 | UAI | The Phylogenetic Indian Buffet Process: A Non-Exchangeable Nonparametric Prior for Latent Features. | Kurt T. Miller, Thomas L. Griffiths, Michael I. Jordan |
| 2007 | ACL | A fully Bayesian approach to unsupervised part-of-speech tagging. | Sharon Goldwater, Thomas L. Griffiths |
| 2007 | NAACL | Bayesian Inference for PCFGs via Markov Chain Monte Carlo. | Mark Johnson, Thomas L. Griffiths, Sharon Goldwater |
| 2006 | AAAI | Learning Systems of Concepts with an Infinite Relational Model. | Charles Kemp, Joshua B. Tenenbaum, Thomas L. Griffiths, Takeshi Yamada, Naonori Ueda |
| 2006 | ACL | Contextual Dependencies in Unsupervised Word Segmentation. | Sharon Goldwater, Thomas L. Griffiths, Mark Johnson |
| 2006 | ACL | Unsupervised Topic Modelling for Multi-Party Spoken Discourse. | Matthew Purver, Konrad P. Krding, Thomas L. Griffiths, Joshua B. Tenenbaum |
| 2006 | UAI | Structured Priors for Structure Learning. | Vikash K. Mansinghka, Charles Kemp, Thomas L. Griffiths, Joshua B. Tenenbaum |
| 2006 | UAI | A Non-Parametric Bayesian Method for Inferring Hidden Causes. | Frank D. Wood, Thomas L. Griffiths, Zoubin Ghahramani |
| 2004 | UAI | The Author-Topic Model for Authors and Documents. | Michal Rosen-Zvi, Thomas L. Griffiths, Mark Steyvers, Padhraic Smyth |