Goodman, Noah

63 publications

TMLR 2026 Large Language Model Reasoning Failures Peiyang Song, Pengrui Han, Noah Goodman

JMLR 2025 Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability Atticus Geiger, Duligur Ibeling, Amir Zur, Maheep Chaudhary, Sonakshi Chauhan, Jing Huang, Aryaman Arora, Zhengxuan Wu, Noah Goodman, Christopher Potts, Thomas Icard

ICLRW 2025 D3: A Large Dataset for Training Code Language Models to Act Diff-by-Diff Ulyana Piterbarg, Kanishk Gandhi, Lerrel Pinto, Noah Goodman, Rob Fergus

ICLR 2025 Eliciting Human Preferences with Language Models Belinda Z. Li, Alex Tamkin, Noah Goodman, Jacob Andreas

TMLR 2025 Emergent Symbol-like Number Variables in Artificial Neural Networks Satchel Grant, Noah Goodman, James Lloyd McClelland

NeurIPS 2025 In-Context Learning Strategies Emerge Rationally Daniel Wurgaft, Ekdeep Singh Lubana, Core Francisco Park, Hidenori Tanaka, Gautam Reddy, Noah Goodman

ICLR 2025 What Makes a Maze Look like a Maze? Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Noah Goodman, Jiajun Wu

ICML 2024 Automated Statistical Model Discovery with Language Models Michael Y. Li, Emily Fox, Noah Goodman

TMLR 2024 Certified Deductive Reasoning with Language Models Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah Goodman

ICML 2024 Codebook Features: Sparse and Discrete Interpretability for Neural Networks Alex Tamkin, Mohammad Taufeeque, Noah Goodman

CLeaR 2024 Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah Goodman

ICLR 2024 Hypothesis Search: Inductive Reasoning with Language Models Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah Goodman

NeurIPSW 2024 MathCAMPS: Fine-Grained Synthesis of Mathematical Problems from Human Curricula Shubhra Mishra, Gabriel Poesia, Belinda Mo, Noah Goodman

NeurIPSW 2024 Policy Dreamer: Diverse Public Policy Generation via Elicitation and Simulation of Human Preferences Arjun Karanam, José Ramón Enríquez, Udari Madhushani Sehwag, Michael Elabd, Kanishk Gandhi, Noah Goodman, Sanmi Koyejo

ICLRW 2024 Symbolic Variables in Distributed Networks That Count Satchel Grant, Zhengxuan Wu, James Lloyd McClelland, Noah Goodman

NeurIPSW 2023 Can Visual Scratchpads with Diagrammatic Abstractions Augment LLM Reasoning? Joy Hsu, Gabriel Poesia, Jiajun Wu, Noah Goodman

NeurIPS 2023 Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning Alex Tamkin, Margalit Glasgow, Xiluo He, Noah Goodman

ICML 2023 Generating Language Corrections for Teaching Physical Control Tasks Megha Srivastava, Noah Goodman, Dorsa Sadigh

NeurIPS 2023 Interpretability at Scale: Identifying Causal Mechanisms in Alpaca Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah Goodman

NeurIPS 2023 Learning to Compress Prompts with Gist Tokens Jesse Mu, Xiang Li, Noah Goodman

NeurIPS 2023 Parsel🐍: Algorithmic Reasoning with Language Models by Composing Decompositions Eric Zelikman, Qian Huang, Gabriel Poesia, Noah Goodman, Nick Haber

NeurIPSW 2023 Social Contract AI: Aligning AI Assistants with Implicit Group Norms Jan-Philipp Fränken, Samuel Kwok, Peixuan Ye, Kanishk Gandhi, Dilip Arumugam, Jared Moore, Alex Tamkin, Tobias Gerstenberg, Noah Goodman

NeurIPSW 2023 Solving Math Word Problems by Combining Language Models with Symbolic Solvers Joy He-Yueya, Gabriel Poesia, Rose Wang, Noah Goodman

NeurIPSW 2023 Strategic Reasoning with Language Models Kanishk Gandhi, Dorsa Sadigh, Noah Goodman

ICLR 2023 Task Ambiguity in Humans and Language Models Alex Tamkin, Kunal Handa, Avash Shrestha, Noah Goodman

NeurIPS 2023 Understanding Social Reasoning in Language Models with Language Models Kanishk Gandhi, Jan-Philipp Fraenken, Tobias Gerstenberg, Noah Goodman

NeurIPS 2023 Why Think Step by Step? Reasoning Emerges from the Locality of Experience Ben Prystawski, Michael Li, Noah Goodman

NeurIPS 2022 Active Learning Helps Pretrained Models Learn the Intended Task Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah Goodman

NeurIPS 2022 Assistive Teaching of Motor Control Tasks to Humans Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah Goodman, Dorsa Sadigh

NeurIPS 2022 CLEVRER-Humans: Describing Physical and Causal Events the Human Way Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah Goodman, Jiajun Wu

NeurIPS 2022 DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah Goodman

ICLRW 2022 Emergent Covert Signaling in Adversarial Reference Games Dhara Yu, Jesse Mu, Noah Goodman

NeurIPS 2022 Foundation Posteriors for Approximate Probabilistic Inference Mike Wu, Noah Goodman

NeurIPS 2022 Geoclidean: Few-Shot Generalization in Euclidean Geometry Joy Hsu, Jiajun Wu, Noah Goodman

NeurIPS 2022 Improving Intrinsic Exploration with Language Abstractions Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah Goodman, Tim Rocktäschel, Edward Grefenstette

NeurIPSW 2022 In the ZONE: Measuring Difficulty and Progression in Curriculum Generation Rose E Wang, Jesse Mu, Dilip Arumugam, Natasha Jaques, Noah Goodman

ICML 2022 Inducing Causal Structure for Interpretable Neural Networks Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah Goodman, Christopher Potts

ICLRW 2022 Know Thy Student: Interactive Learning with Gaussian Processes Rose E Wang, Mike Wu, Noah Goodman

ICLR 2022 Language Modeling via Stochastic Processes Rose E Wang, Esin Durmus, Noah Goodman, Tatsunori Hashimoto

NeurIPSW 2022 On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning Dilip Arumugam, Mark K Ho, Noah Goodman, Benjamin Van Roy

NeurIPS 2022 STaR: Bootstrapping Reasoning with Reasoning Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah Goodman

ICLR 2021 Conditional Negative Sampling for Contrastive Learning of Visual Representations Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah Goodman

NeurIPS 2021 Contrastive Reinforcement Learning of Symbolic Reasoning Domains Gabriel Poesia, WenXin Dong, Noah Goodman

NeurIPS 2021 Emergent Communication of Generalizations Jesse Mu, Noah Goodman

NeurIPS 2021 Improving Compositionality of Neural Networks by Decoding Representations to Inputs Mike Wu, Noah Goodman, Stefano Ermon

ICLR 2021 Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin, Mike Wu, Noah Goodman

NeurIPS 2020 Language Through a Prism: A Spectral Approach for Multiscale Language Representations Alex Tamkin, Dan Jurafsky, Noah Goodman

ICMLW 2019 Continual Adaptation for Efficient Machine Communication Robert Hawkins, Minae Kwon, Dorsa Sadigh, Noah Goodman

AISTATS 2019 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference Mike Wu, Noah Goodman, Stefano Ermon

ICML 2019 Tensor Variable Elimination for Plated Factor Graphs Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Neeraj Pradhan, Justin Chiu, Alexander Rush, Noah Goodman

NeurIPS 2019 Variational Bayesian Optimal Experimental Design Adam Foster, Martin Jankowiak, Elias Bingham, Paul Horsfall, Yee Whye Teh, Thomas Rainforth, Noah Goodman

NeurIPS 2018 Bias and Generalization in Deep Generative Models: An Empirical Study Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah Goodman, Stefano Ermon

NeurIPS 2018 Multimodal Generative Models for Scalable Weakly-Supervised Learning Mike Wu, Noah Goodman

NeurIPS 2017 Learning Disentangled Representations with Semi-Supervised Deep Generative Models Siddharth N, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah Goodman, Pushmeet Kohli, Frank Wood, Philip Torr

NeurIPS 2016 Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs Using Neural Networks Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah Goodman

NeurIPS 2013 Learning Stochastic Inverses Andreas Stuhlmüller, Jacob Taylor, Noah Goodman

NeurIPS 2013 Learning and Using Language via Recursive Pragmatic Reasoning About Other Agents Nathaniel J Smith, Noah Goodman, Michael Frank

NeurIPS 2012 Burn-in, Bias, and the Rationality of Anchoring Falk Lieder, Tom Griffiths, Noah Goodman

AISTATS 2011 Lightweight Implementations of Probabilistic Programming Languages via Transformational Compilation David Wingate, Andreas Stuhlmueller, Noah Goodman

NeurIPS 2011 Nonstandard Interpretations of Probabilistic Programs for Efficient Inference David Wingate, Noah Goodman, Andreas Stuhlmueller, Jeffrey M. Siskind

NeurIPS 2009 Help or Hinder: Bayesian Models of Social Goal Inference Tomer Ullman, Chris Baker, Owen Macindoe, Owain Evans, Noah Goodman, Joshua B. Tenenbaum

NeurIPS 2007 A Bayesian Framework for Cross-Situational Word-Learning Noah Goodman, Joshua B. Tenenbaum, Michael J. Black

NeurIPS 2007 Learning and Using Relational Theories Charles Kemp, Noah Goodman, Joshua B. Tenenbaum