| 2025 | CogSci | Language and Experience: A Computational Model of Social Learning in Complex Novel Tasks. | Cdric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah D. Goodman, Jacob Andreas, Joshua B. Tenenbaum |
| 2025 | CogSci | Thinking fast, slow, and everywhere in between in humans and language models. | Ben Prystawski, Noah D. Goodman |
| 2025 | CogSci | Non-literal Understanding of Number Words by Language Models. | Polina Tsvilodub, Kanishk Gandhi, Haoran Zhao, Jan-Philipp Frnken, Michael Franke, Noah D. Goodman |
| 2025 | CogSci | Scaling up the think-aloud method. | Daniel Wurgaft, Ben Prystawski, Kanishk Gandhi, Cedegao E. Zhang, Joshua B. Tenenbaum, Noah D. Goodman |
| 2025 | EMNLP | Value Profiles for Encoding Human Variation. | Taylor Sorensen, Pushkar Mishra, Roma Patel, Michael Henry Tessler, Michiel A. Bakker, Georgina Evans, Iason Gabriel, Noah D. Goodman, Verena Rieser |
| 2025 | ICLR | What Makes a Maze Look Like a Maze? | Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Noah D. Goodman, Jiajun Wu |
| 2025 | ICLR | Eliciting Human Preferences with Language Models. | Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas |
| 2024 | CogSci | Naturalistic Transmission of Causal Knowledge between Machines and Humans. | Cdric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah D. Goodman, Jacob Andreas, Josh Tenenbaum |
| 2024 | CogSci | Procedural Dilemma Generation for Moral Reasoning in Humans and Language Models. | Jan-Philipp Frnken, Kanishk Gandhi, Tori Qiu, Ayesha Khawaja, Noah D. Goodman, Tobias Gerstenberg |
| 2024 | CogSci | Symbolic Variables in Distributed Networks that Count. | Satchel Grant, Zhengxuan Wu, Jay McClelland, Noah D. Goodman |
| 2024 | EACL | Backtracing: Retrieving the Cause of the Query. | Rose E. Wang, Pawan Wirawarn, Omar Khattab, Noah D. Goodman, Dorottya Demszky |
| 2024 | EDM | Evaluating and Optimizing Educational Content with Large Language Model Judgments. | Joy He-Yueya, Noah D. Goodman, Emma Brunskill |
| 2024 | EMNLP | Is Child-Directed Speech Effective Training Data for Language Models? | Steven Y. Feng, Noah D. Goodman, Michael Frank |
| 2024 | ICLR | Hypothesis Search: Inductive Reasoning with Language Models. | Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman |
| 2024 | ICML | Automated Statistical Model Discovery with Language Models. | Michael Y. Li, Emily B. Fox, Noah D. Goodman |
| 2024 | ICML | Codebook Features: Sparse and Discrete Interpretability for Neural Networks. | Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman |
| 2024 | NAACL | pyvene: A Library for Understanding and Improving PyTorch Models via Interventions. | Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts |
| 2023 | CogSci | Cultural reinforcement learning: a framework for modeling cumulative culture on a limited channel. | Ben Prystawski, Dilip Arumugam, Noah D. Goodman |
| 2023 | CogSci | Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models. | Ben Prystawski, Paul H. Thibodeau, Christopher Potts, Noah D. Goodman |
| 2023 | CogSci | Overinformative Question Answering by Humans and Machines. | Polina Tsvilodub, Michael Franke, Robert D. Hawkins, Noah D. Goodman |
| 2023 | CogSci | Characterizing tradeoffs between teaching via language and demonstrations in multi-agent systems. | Dhara Yu, Noah D. Goodman, Jesse Mu |
| 2023 | CVPR | Multispectral Contrastive Learning with Viewmaker Networks. | Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin |
| 2023 | ICLR | Task Ambiguity in Humans and Language Models. | Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman |
| 2023 | ICML | Generating Language Corrections for Teaching Physical Control Tasks. | Megha Srivastava, Noah D. Goodman, Dorsa Sadigh |
| 2022 | CogSci | Automated generation of sentence reading fluency test items. | Julia White, Amy Burkhardt, Jason D. Yeatman, Noah D. Goodman |
| 2022 | CogSci | Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning. | Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, Elisa Kreiss |
| 2022 | CogSci | Two's company but six is a crowd: emergence of conventions in multiparty communication games. | Veronica Boyce, Robert D. Hawkins, Noah D. Goodman, Michael C. Frank |
| 2022 | CogSci | Left to the Reader: Abstracting Solutions in Mathematical Reasoning. | Gabriel Poesia Reis e Silva, Noah D. Goodman |
| 2022 | EMNLP | Mixed-effects transformers for hierarchical adaptation. | Julia White, Noah D. Goodman, Robert X. D. Hawkins |
| 2022 | EMNLP | Concadia: Towards Image-Based Text Generation with a Purpose. | Elisa Kreiss, Fei Fang, Noah D. Goodman, Christopher Potts |
| 2022 | ICLR | Language modeling via stochastic processes. | Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto |
| 2022 | ICML | Inducing Causal Structure for Interpretable Neural Networks. | Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts |
| 2022 | NAACL | Causal Distillation for Language Models. | Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman |
| 2021 | AAAI | Pragmatic Code Autocomplete. | Gabriel Poesia, Noah D. Goodman |
| 2021 | ACL | Question Generation for Adaptive Education. | Megha Srivastava, Noah D. Goodman |
| 2021 | EDM | Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. | Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech |
| 2021 | EMNLP | Calibrate your listeners! Robust communication-based training for pragmatic speakers. | Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman |
| 2021 | EMNLP | Open-domain clarification question generation without question examples. | Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman |
| 2021 | ICLR | Viewmaker Networks: Learning Views for Unsupervised Representation Learning. | Alex Tamkin, Mike Wu, Noah D. Goodman |
| 2021 | ICLR | Conditional Negative Sampling for Contrastive Learning of Visual Representations. | Mike Wu, Milan Moss, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman |
| 2020 | AAAI | Meta-Amortized Variational Inference and Learning. | Mike Wu, Kristy Choi, Noah D. Goodman, Stefano Ermon |
| 2020 | ACL | Shaping Visual Representations with Language for Few-Shot Classification. | Jesse Mu, Percy Liang, Noah D. Goodman |
| 2020 | CogSci | Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks. | Robert X. D. Hawkins, Noah D. Goodman, Adele E. Goldberg, Tom Griffiths |
| 2020 | CogSci | Learning to refer informatively by amortizing pragmatic reasoning. | Julia White, Jesse Mu, Noah D. Goodman |
| 2020 | CoNLL | Continual Adaptation for Efficient Machine Communication. | Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman |
| 2020 | EDM | Variational Item Response Theory: Fast, Accurate, and Expressive. | Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman |
| 2020 | EMNLP | Investigating Transferability in Pretrained Language Models. | Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman |
| 2019 | AAAI | Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference. | Mike Wu, Milan Moss, Noah D. Goodman, Chris Piech |
| 2019 | ACL | Learning from Omission. | Bill McDowell, Noah D. Goodman |
| 2019 | ACL | DisSent: Learning Sentence Representations from Explicit Discourse Relations. | Allen Nie, Erin Bennett, Noah D. Goodman |
| 2019 | AISTATS | Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference. | Mike Wu, Noah D. Goodman, Stefano Ermon |
| 2019 | CogSci | The first crank of the cultural ratchet: Learning and transmitting concepts through language. | Sahil Chopra, Michael Henry Tessler, Noah D. Goodman |
| 2019 | CogSci | Disentangling contributions of visual information and interaction history in the formation of graphical conventions. | Robert X. D. Hawkins, Megumi Sano, Noah D. Goodman, Judith W. Fan |
| 2019 | CogSci | The interactions of rational, pragmatic agents lead to efficient language structure and use. | Benjamin N. Peloquin, Noah D. Goodman, Michael C. Frank |
| 2019 | CogSci | Extending Rationality. | Emmanuel M. Pothos, Jerome R. Busemeyer, Timothy J. Pleskac, James M. Yearsley, Josh Tenenbaum, Noah D. Goodman, Michael Henry Tessler, Tom Griffiths, Falk Lieder, Ralph Hertwig, Thorsten Pachur, Christina Leuker, Richard M. Shiffrin |
| 2019 | ICCV | Shapeglot: Learning Language for Shape Differentiation. | Panos Achlioptas, Leonidas J. Guibas, Noah D. Goodman, Judy Fan, Robert X. D. Hawkins |
| 2019 | ICML | Tensor Variable Elimination for Plated Factor Graphs. | Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Neeraj Pradhan, Justin T. Chiu, Alexander M. Rush, Noah D. Goodman |
| 2019 | NAACL | Lost in Machine Translation: A Method to Reduce Meaning Loss. | Reuben Cohn-Gordon, Noah D. Goodman |
| 2018 | CogSci | An Information-Theoretic Explanation of Adjective Ordering Preferences. | Michael Hahn, Judith Degen, Noah D. Goodman, Dan Jurafsky, Richard Futrell |
| 2018 | CogSci | Evaluating Compositionality in Sentence Embeddings. | Ishita Dasgupta, Demi Guo, Andreas Stuhlmller, Samuel Gershman, Noah D. Goodman |
| 2018 | CogSci | Emerging abstractions: Lexical conventions are shaped by communicative context. | Robert X. D. Hawkins, Michael Franke, Kenny Smith, Noah D. Goodman |
| 2018 | CogSci | webppl-oed: A practical optimal experiment design system. | Long Ouyang, Michael Henry Tessler, Daniel Ly, Noah D. Goodman |
| 2018 | CogSci | Deriving uniform information density behavior in pragmatic agents. | Benjamin N. Peloquin, Noah D. Goodman, Michael C. Frank |
| 2018 | CogSci | Statistics as Pottery: Bayesian Data Analysis using Probabilistic Programs. | Michael Henry Tessler, Noah D. Goodman |
| 2018 | CogSci | Generalizations, from representation to transmission. | Michael Henry Tessler, Noah D. Goodman, David Danks, Emily Foster-Hanson, Marjorie Rhodes, Greg Carlson |
| 2018 | NAACL | Pragmatically Informative Image Captioning with Character-Level Inference. | Reuben Cohn-Gordon, Noah D. Goodman, Christopher Potts |
| 2017 | CogSci | Amortized Hypothesis Generation. | Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman |
| 2017 | CogSci | Convention-formation in iterated reference games. | Robert X. D. Hawkins, Mike Frank, Noah D. Goodman |
| 2017 | CogSci | Mentioning atypical properties of objects is communicatively efficient. | Elisa Kreiss, Robert X. D. Hawkins, Judith Degen, Noah D. Goodman |
| 2017 | CogSci | Warm (for winter): Comparison class understanding in vague language. | Michael Henry Tessler, Michael Lopez-Brau, Noah D. Goodman |
| 2017 | CogSci | "I won't lie, it wasn't amazing": Modeling polite indirect speech. | Erica J. Yoon, Michael Henry Tessler, Noah D. Goodman, Michael C. Frank |
| 2016 | AAAI | Learning the Preferences of Ignorant, Inconsistent Agents. | Owain Evans, Andreas Stuhlmller, Noah D. Goodman |
| 2016 | AISTATS | C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching. | Daniel Ritchie, Andreas Stuhlmller, Noah D. Goodman |
| 2016 | CogSci | What does the crowd believe? A hierarchical approach to estimating subjective beliefs from empirical data. | Michael Franke, Fabian Dablander, Anthea Schller, Erin Bennett, Judith Degen, Michael Henry Tessler, Justine T. Kao, Noah D. Goodman |
| 2016 | CogSci | Animal, dog, or dalmatian? Level of abstraction in nominal referring expressions. | Caroline Graf, Judith Degen, Robert X. D. Hawkins, Noah D. Goodman |
| 2016 | CogSci | Conversational expectations account for apparent limits on theory of mind use. | Robert X. D. Hawkins, Noah D. Goodman |
| 2016 | CogSci | The Emergence of Conventions. | Robert X. D. Hawkins, Noah D. Goodman, Olga Feher, Kenny Smith, Robert L. Goldstone, Tom Griffiths |
| 2016 | CogSci | Empirical and Computational Approaches to Metaphor and Figurative Meaning. | Justine T. Kao, Noah D. Goodman |
| 2016 | CogSci | Emotions in lay explanations of behavior. | Desmond C. Ong, Jamil Zaki, Noah D. Goodman |
| 2016 | CogSci | A rational speech-act model of projective content. | Ciyang Qing, Noah D. Goodman, Daniel Lassiter |
| 2016 | CogSci | Communicating generalizations about events. | Michael Henry Tessler, Noah D. Goodman |
| 2016 | CogSci | The Pragmatics of Spatial Language. | Tomer D. Ullman, Yang Xu, Noah D. Goodman |
| 2016 | CogSci | Talking with tact: Polite language as a balance between informativity and kindness. | Erica J. Yoon, Michael Henry Tessler, Noah D. Goodman, Michael C. Frank |
| 2016 | EMNLP | Learning to Generate Compositional Color Descriptions. | Will Monroe, Noah D. Goodman, Christopher Potts |
| 2015 | CogSci | Not by number alone: The effect of teachers' knowledge and its value in evaluating "sins of omission". | Ilona Bass, Daniel Hawthorne, Noah D. Goodman, Hyowon Gweon |
| 2015 | CogSci | Extremely costly intensifiers are stronger than quite costly ones. | Erin Bennett, Noah D. Goodman |
| 2015 | CogSci | Wonky worlds: Listeners revise world knowledge when utterances are odd. | Judith Degen, Michael Henry Tessler, Noah D. Goodman |
| 2015 | CogSci | How, whether, why: Causal judgments as counterfactual contrasts. | Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum |
| 2015 | CogSci | Why do you ask? Good questions provoke informative answers. | Robert X. D. Hawkins, Andreas Stuhlmller, Judith Degen, Noah D. Goodman |
| 2015 | CogSci | So good it has to be true: Wishful thinking in theory of mind. | Daniel Hawthorne-Madell, Noah D. Goodman |
| 2015 | CogSci | A Resource-Rational Approach to the Causal Frame Problem. | Thomas Icard, Noah D. Goodman |
| 2015 | CogSci | Let's talk (ironically) about the weather: Modeling verbal irony. | Justine T. Kao, Noah D. Goodman |
| 2015 | CogSci | Emergent Collective Sensing in Human Groups. | Peter M. Krafft, Robert X. D. Hawkins, Alex Pentland, Noah D. Goodman, Joshua B. Tenenbaum |
| 2015 | CogSci | Near-misses sting even when they are uncontrollable. | Desmond C. Ong, Noah D. Goodman, Jamil Zaki |
| 2015 | CogSci | Toddlers Always Get the Last Word: Recency biases in early verbal behavior. | Emily Sumner, Erika DeAngelis, Mara Hyatt, Noah D. Goodman, Celeste Kidd |
| 2014 | AISTATS | Generating Efficient MCMC Kernels from Probabilistic Programs. | Lingfeng Yang, Pat Hanrahan, Noah D. Goodman |
| 2014 | CogSci | The strategic use of noise in pragmatic reasoning. | Leon Bergen, Noah D. Goodman |
| 2014 | CogSci | Lost your marbles? The puzzle of dependent measures in experimental pragmatics. | Judith Degen, Noah D. Goodman |
| 2014 | CogSci | Symposium: The Role of Alternatives in Pragmatic Inference. | Judith Degen, Noah D. Goodman, Roni Katzir, David Barner, Albert Gatt |
| 2014 | CogSci | Amortized Inference in Probabilistic Reasoning. | Samuel Gershman, Noah D. Goodman |
| 2014 | CogSci | From counterfactual simulation to causal judgment. | Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum |
| 2014 | CogSci | Probability, programs, and the mind: Building structured Bayesian models of cognition. | Noah D. Goodman, Joshua B. Tenenbaum |
| 2014 | CogSci | Formalizing the Pragmatics of Metaphor Understanding. | Justine T. Kao, Leon Bergen, Noah D. Goodman |
| 2014 | CogSci | Understanding Affective Cognition: Frontiers in modeling reasoning about others' emotions. | Desmond C. Ong, Jamil Zaki, Noah D. Goodman |
| 2014 | CogSci | Some arguments are probably valid: Syllogistic reasoning as communication. | Michael Henry Tessler, Noah D. Goodman |
| 2014 | CogSci | Learning physical theories from dynamical scenes. | Tomer D. Ullman, Andreas Stuhlmller, Noah D. Goodman, Joshua B. Tenenbaum |
| 2013 | CogSci | The Funny Thing About Incongruity: A Computational Model of Humor in Puns. | Justine T. Kao, Roger Levy, Noah D. Goodman |
| 2013 | CogSci | Learned helplessness and generalization. | Falk Lieder, Noah D. Goodman, Quentin J. M. Huys |
| 2013 | CogSci | Minimal Nativism: How does cognitive development get off the ground? | Tomer D. Ullman, Joshua B. Tenenbaum, Noah D. Goodman, Shimon Ullman, Elizabeth S. Spelke |
| 2013 | POPL | The principles and practice of probabilistic programming. | Noah D. Goodman |
| 2012 | CogSci | That's what she (could have) said: How alternative utterances affect language use. | Leon Bergen, Noah D. Goodman, Roger Levy |
| 2012 | CogSci | Ping Pong in Church: Productive use of concepts in human probabilistic inference. | Tobias Gerstenberg, Noah D. Goodman |
| 2012 | CogSci | Noisy Newtons: Unifying process and dependency accounts of causal attribution. | Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum |
| 2012 | CogSci | Knowledge and implicature: Modeling language understanding as social cognition. | Noah D. Goodman, Andreas Stuhlmller |
| 2012 | CogSci | Probability, programs, and the mind: Building structured Bayesian models of cognition. | Noah D. Goodman, Joshua B. Tenenbaum |
| 2012 | CogSci | How many kinds of reasoning? Inference, probability, and natural language semantics. | Daniel Lassiter, Noah D. Goodman |
| 2012 | UIST | Learning design patterns with bayesian grammar induction. | Jerry O. Talton, Lingfeng Yang, Ranjitha Kumar, Maxine Lim, Noah D. Goodman, Radomr Mech |
| 2011 | CogSci | Productivity and Reuse in Language. | Timothy J. O'Donnell, Jesse Snedeker, Joshua B. Tenenbaum, Noah D. Goodman |
| 2011 | CogSci | Productivity and Reuse in Language: a Developmental Study. | Timothy J. O'Donnell, Jesse Snedeker, Joshua B. Tenenbaum, Noah D. Goodman |
| 2011 | CogSci | Ad-hoc scalar implicature in adults and children. | Alex Stiller, Noah D. Goodman, Michael C. Frank |
| 2011 | CogSci | Forward Physics: How people learn and generalize novel dynamical models. | Tomer D. Ullman, Noah D. Goodman, Josh Tenenbaum |
| 2011 | IJCAI | Bayesian Policy Search with Policy Priors. | David Wingate, Noah D. Goodman, Daniel M. Roy, Leslie Pack Kaelbling, Joshua B. Tenenbaum |
| 2009 | UAI | The Infinite Latent Events Model. | David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum |
| 2008 | UAI | Church: a language for generative models. | Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum |