Noah D. Goodman

335 papers A* 50A 6B 81Journal 169Unranked 29
YearRankTypeTitle / Venue / Authors
2026 J jnl
Endless Terminals: Scaling RL Environments for Terminal Agents.
CoRR
Kanishk Gandhi, Shivam Garg, Noah D. Goodman, Dimitris Papailiopoulos
2026 J jnl
Learning to Simulate Human Dialogue.
CoRR
Kanishk Gandhi, Agam Bhatia, Noah D. Goodman
2025 J jnl
An Approach to Technical AGI Safety and Security.
CoRR
Rohin Shah, Alex Irpan, Alexander Matt Turner, Anna Wang, Arthur Conmy, David Lindner, Jonah Brown-Cohen, Lewis Ho, Neel Nanda, Raluca Ada Popa, Rishub Jain, Rory Greig, Samuel Albanie, Scott Emmons, Sebastian Farquhar, Sébastien Krier, Senthooran Rajamanoharan, Sophie Bridgers, Tobi Ijitoye, Tom Everitt, Victoria Krakovna, Vikrant Varma, Vladimir Mikulik, Zachary Kenton, Dave Orr, Shane Legg, Noah D. Goodman, Allan Dafoe, Four Flynn, Anca D. Dragan
2025 J jnl
Automated Discovery of Tactic Libraries for Interactive Theorem Proving.
CoRR
Yutong Xin, Jimmy Xin, Gabriel Poesia, Noah D. Goodman, Qiaochu Chen, Isil Dillig
2025 J jnl
Automated Discovery of Tactic Libraries for Interactive Theorem Proving.
Proc. ACM Program. Lang.
Yutong Xin, Jimmy Xin, Gabriel Poesia, Noah D. Goodman, Qiaochu Chen, Isil Dillig
2025 J jnl
Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering.
CoRR
Eric J. Bigelow, Daniel Wurgaft, YingQiao Wang, Noah D. Goodman, Tomer D. Ullman, Hidenori Tanaka, Ekdeep Singh Lubana
2025 J jnl
BoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery.
CoRR
Kanishk Gandhi, Michael Y. Li, Lyle Goodyear, Louise Li, Aditi Bhaskar, Mohammed Zaman, Noah D. Goodman
2025 J jnl
Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability.
J. Mach. Learn. Res.
Atticus Geiger, Duligur Ibeling, Amir Zur, Maheep Chaudhary, Sonakshi Chauhan, Jing Huang, Aryaman Arora, Zhengxuan Wu, Noah D. Goodman, Christopher Potts, Thomas Icard
2025 J jnl
Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.
CoRR
Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, Nathan Lile, Noah D. Goodman
2025 A* conf
Eliciting Human Preferences with Language Models.
ICLR
Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas
2025 J jnl
Emergent Symbol-like Number Variables in Artificial Neural Networks.
CoRR
Satchel Grant, Noah D. Goodman, James L. McClelland
2025 J jnl
In-Context Learning Strategies Emerge Rationally.
CoRR
Daniel Wurgaft, Ekdeep Singh Lubana, Core Francisco Park, Hidenori Tanaka, Gautam Reddy, Noah D. Goodman
2025 B conf
Language and Experience: A Computational Model of Social Learning in Complex Novel Tasks.
CogSci
Cédric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah D. Goodman, Jacob Andreas, Joshua B. Tenenbaum
2025 J jnl
Language and Experience: A Computational Model of Social Learning in Complex Tasks.
CoRR
Cédric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah D. Goodman, Jacob Andreas, Joshua B. Tenenbaum
2025 J jnl
Lossy communication constrains iterated learning.
CoRR
Ben Prystawski, Dilip Arumugam, Noah D. Goodman
2025 B conf
Non-literal Understanding of Number Words by Language Models.
CogSci
Polina Tsvilodub, Kanishk Gandhi, Haoran Zhao, Jan-Philipp Fränken, Michael Franke, Noah D. Goodman
2025 J jnl
Non-literal Understanding of Number Words by Language Models.
CoRR
Polina Tsvilodub, Kanishk Gandhi, Haoran Zhao, Jan-Philipp Fränken, Michael Franke, Noah D. Goodman
2025 J jnl
Resource Rational Contractualism Should Guide AI Alignment.
CoRR
Sydney Levine, Matija Franklin, Tan Zhi-Xuan, Secil Yanik Guyot, Lionel Wong, Daniel Kilov, Yejin Choi, Joshua B. Tenenbaum, Noah D. Goodman, Seth Lazar, Iason Gabriel
2025 B conf
Scaling up the think-aloud method.
CogSci
Daniel Wurgaft, Ben Prystawski, Kanishk Gandhi, Cedegao E. Zhang, Joshua B. Tenenbaum, Noah D. Goodman
2025 J jnl
Scaling up the think-aloud method.
CoRR
Daniel Wurgaft, Ben Prystawski, Kanishk Gandhi, Cedegao E. Zhang, Joshua B. Tenenbaum, Noah D. Goodman
2025 B conf
Thinking fast, slow, and everywhere in between in humans and language models.
CogSci
Ben Prystawski, Noah D. Goodman
2025 A* conf
Value Profiles for Encoding Human Variation.
EMNLP
Taylor Sorensen, Pushkar Mishra, Roma Patel, Michael Henry Tessler, Michiel A. Bakker, Georgina Evans, Iason Gabriel, Noah D. Goodman, Verena Rieser
2025 J jnl
Value Profiles for Encoding Human Variation.
CoRR
Taylor Sorensen, Pushkar Mishra, Roma Patel, Michael Henry Tessler, Michiel A. Bakker, Georgina Evans, Iason Gabriel, Noah D. Goodman, Verena Rieser
2025 A* conf
What Makes a Maze Look Like a Maze?
ICLR
Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Noah D. Goodman, Jiajun Wu
2024 J jnl
A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments.
CoRR
Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman
2024 A* conf
Automated Statistical Model Discovery with Language Models.
ICML
Michael Y. Li, Emily B. Fox, Noah D. Goodman
2024 J jnl
Automated Statistical Model Discovery with Language Models.
CoRR
Michael Y. Li, Emily B. Fox, Noah D. Goodman
2024 — conf
Backtracing: Retrieving the Cause of the Query.
EACL (Findings)
Rose E. Wang, Pawan Wirawarn, Omar Khattab, Noah D. Goodman, Dorottya Demszky
2024 J jnl
Backtracing: Retrieving the Cause of the Query.
CoRR
Rose E. Wang, Pawan Wirawarn, Omar Khattab, Noah D. Goodman, Dorottya Demszky
2024 J jnl
Bayesian Preference Elicitation with Language Models.
CoRR
Kunal Handa, Yarin Gal, Ellie Pavlick, Noah D. Goodman, Jacob Andreas, Alex Tamkin, Belinda Z. Li
2024 J jnl
Bayesian scaling laws for in-context learning.
CoRR
Aryaman Arora, Dan Jurafsky, Christopher Potts, Noah D. Goodman
2024 J jnl
Certified Deductive Reasoning with Language Models.
Trans. Mach. Learn. Res.
Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman
2024 A* conf
Codebook Features: Sparse and Discrete Interpretability for Neural Networks.
ICML
Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman
2024 J jnl
CriticAL: Critic Automation with Language Models.
CoRR
Michael Y. Li, Vivek Vajipey, Noah D. Goodman, Emily B. Fox
2024 B conf
Evaluating and Optimizing Educational Content with Large Language Model Judgments.
EDM
Joy He-Yueya, Noah D. Goodman, Emma Brunskill
2024 J jnl
Evaluating and Optimizing Educational Content with Large Language Model Judgments.
CoRR
Joy He-Yueya, Noah D. Goodman, Emma Brunskill
2024 — conf
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations.
CLeaR
Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman
2024 J jnl
Human-like Affective Cognition in Foundation Models.
CoRR
Kanishk Gandhi, Zoe Lynch, Jan-Philipp Fränken, Kayla Patterson, Sharon Wambu, Tobias Gerstenberg, Desmond C. Ong, Noah D. Goodman
2024 A* conf
Hypothesis Search: Inductive Reasoning with Language Models.
ICLR
Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman
2024 A* conf
Is Child-Directed Speech Effective Training Data for Language Models?
EMNLP
Steven Y. Feng, Noah D. Goodman, Michael Frank
2024 J jnl
Is Child-Directed Speech Effective Training Data for Language Models?
CoRR
Steven Y. Feng, Noah D. Goodman, Michael C. Frank
2024 A* conf
Learning Formal Mathematics From Intrinsic Motivation.
NeurIPS
Gabriel Poesia, David Broman, Nick Haber, Noah D. Goodman
2024 J jnl
Learning Formal Mathematics From Intrinsic Motivation.
CoRR
Gabriel Poesia, David Broman, Nick Haber, Noah D. Goodman
2024 J jnl
MathCAMPS: Fine-grained Synthesis of Mathematical Problems From Human Curricula.
CoRR
Shubhra Mishra, Gabriel Poesia, Belinda Mo, Noah D. Goodman
2024 B conf
Naturalistic Transmission of Causal Knowledge between Machines and Humans.
CogSci
Cédric Colas, Tracey Mills, Ben Prystawski, Michael Henry Tessler, Noah D. Goodman, Jacob Andreas, Josh Tenenbaum
2024 A* conf
On scalable oversight with weak LLMs judging strong LLMs.
NeurIPS
Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah
2024 J jnl
On scalable oversight with weak LLMs judging strong LLMs.
CoRR
Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah
2024 J jnl
Procedural Dilemma Generation for Evaluating Moral Reasoning in Humans and Language Models.
CoRR
Jan-Philipp Fränken, Kanishk Gandhi, Tori Qiu, Ayesha Khawaja, Noah D. Goodman, Tobias Gerstenberg
2024 B conf
Procedural Dilemma Generation for Moral Reasoning in Humans and Language Models.
CogSci
Jan-Philipp Fränken, Kanishk Gandhi, Tori Qiu, Ayesha Khawaja, Noah D. Goodman, Tobias Gerstenberg
2024 J jnl
Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models.
CoRR
Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, Benjamin W. Domingue, Emma Brunskill, Noah D. Goodman
2024 J jnl
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking.
CoRR
Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, Noah D. Goodman
2024 J jnl
STaR-GATE: Teaching Language Models to Ask Clarifying Questions.
CoRR
Chinmaya Andukuri, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman
2024 A* conf
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels.
NeurIPS
Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov, Kanishk Gandhi, Tobias Gerstenberg, Noah D. Goodman
2024 J jnl
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels.
CoRR
Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov, Kanishk Gandhi, Tobias Gerstenberg, Noah D. Goodman
2024 J jnl
Stream of Search (SoS): Learning to Search in Language.
CoRR
Kanishk Gandhi, Denise Lee, Gabriel Grand, Muxin Liu, Winson Cheng, Archit Sharma, Noah D. Goodman
2024 B conf
Symbolic Variables in Distributed Networks that Count.
CogSci
Satchel Grant, Zhengxuan Wu, Jay McClelland, Noah D. Goodman
2024 J jnl
What Makes a Maze Look Like a Maze?
CoRR
Joy Hsu, Jiayuan Mao, Joshua B. Tenenbaum, Noah D. Goodman, Jiajun Wu
2024 — conf
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions.
NAACL (Demonstrations)
Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts
2024 J jnl
pyvene: A Library for Understanding and Improving PyTorch Models via Interventions.
CoRR
Zhengxuan Wu, Atticus Geiger, Aryaman Arora, Jing Huang, Zheng Wang, Noah D. Goodman, Christopher D. Manning, Christopher Potts
2023 J jnl
Bayesian Reinforcement Learning with Limited Cognitive Load.
CoRR
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
2023 J jnl
CLEVRER-Humans: Describing Physical and Causal Events the Human Way.
CoRR
Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah D. Goodman, Jiajun Wu
2023 — conf
Can Visual Scratchpads With Diagrammatic Abstractions Augment LLM Reasoning?
ICBINB
Joy Hsu, Gabriel Poesia, Jiajun Wu, Noah D. Goodman
2023 J jnl
Certified Reasoning with Language Models.
CoRR
Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman
2023 B conf
Characterizing tradeoffs between teaching via language and demonstrations in multi-agent systems.
CogSci
Dhara Yu, Noah D. Goodman, Jesse Mu
2023 J jnl
Characterizing tradeoffs between teaching via language and demonstrations in multi-agent systems.
CoRR
Dhara Yu, Noah D. Goodman, Jesse Mu
2023 J jnl
Codebook Features: Sparse and Discrete Interpretability for Neural Networks.
CoRR
Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman
2023 B conf
Cultural reinforcement learning: a framework for modeling cumulative culture on a limited channel.
CogSci
Ben Prystawski, Dilip Arumugam, Noah D. Goodman
2023 J jnl
Eliciting Human Preferences with Language Models.
CoRR
Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas
2023 A* conf
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning.
NeurIPS
Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
2023 J jnl
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations.
CoRR
Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman
2023 J jnl
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought.
CoRR
Lionel Wong, Gabriel Grand, Alexander K. Lew, Noah D. Goodman, Vikash K. Mansinghka, Jacob Andreas, Joshua B. Tenenbaum
2023 A* conf
Generating Language Corrections for Teaching Physical Control Tasks.
ICML
Megha Srivastava, Noah D. Goodman, Dorsa Sadigh
2023 J jnl
Generating Language Corrections for Teaching Physical Control Tasks.
CoRR
Megha Srivastava, Noah D. Goodman, Dorsa Sadigh
2023 J jnl
Hypothesis Search: Inductive Reasoning with Language Models.
CoRR
Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman
2023 A* conf
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca.
NeurIPS
Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman
2023 J jnl
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca.
CoRR
Zhengxuan Wu, Atticus Geiger, Christopher Potts, Noah D. Goodman
2023 J jnl
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness.
CoRR
Eric Zelikman, Qian Huang, Percy Liang, Nick Haber, Noah D. Goodman
2023 A* conf
Learning to Compress Prompts with Gist Tokens.
NeurIPS
Jesse Mu, Xiang Li, Noah D. Goodman
2023 J jnl
Learning to Compress Prompts with Gist Tokens.
CoRR
Jesse Mu, Xiang Lisa Li, Noah D. Goodman
2023 — conf
Multispectral Contrastive Learning with Viewmaker Networks.
CVPR Workshops
Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
2023 J jnl
Multispectral Self-Supervised Learning with Viewmaker Networks.
CoRR
Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
2023 B conf
Overinformative Question Answering by Humans and Machines.
CogSci
Polina Tsvilodub, Michael Franke, Robert D. Hawkins, Noah D. Goodman
2023 J jnl
Overinformative Question Answering by Humans and Machines.
CoRR
Polina Tsvilodub, Michael Franke, Robert D. Hawkins, Noah D. Goodman
2023 A* conf
Parsel🦆: Algorithmic Reasoning with Language Models by Composing Decompositions.
NeurIPS
Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber
2023 B conf
Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models.
CogSci
Ben Prystawski, Paul H. Thibodeau, Christopher Potts, Noah D. Goodman
2023 — conf
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts.
BEA@ACL
Rose E. Wang, Pawan Wirawarn, Noah D. Goodman, Dorottya Demszky
2023 J jnl
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts.
CoRR
Rose E. Wang, Pawan Wirawarn, Noah D. Goodman, Dorottya Demszky
2023 J jnl
Social Contract AI: Aligning AI Assistants with Implicit Group Norms.
CoRR
Jan-Philipp Fränken, Sam Kwok, Peixuan Ye, Kanishk Gandhi, Dilip Arumugam, Jared Moore, Alex Tamkin, Tobias Gerstenberg, Noah D. Goodman
2023 J jnl
Solving Math Word Problems by Combining Language Models With Symbolic Solvers.
CoRR
Joy He-Yueya, Gabriel Poesia, Rose E. Wang, Noah D. Goodman
2023 J jnl
Strategic Reasoning with Language Models.
CoRR
Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman
2023 A* conf
Task Ambiguity in Humans and Language Models.
ICLR
Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman
2023 A* conf
Understanding Social Reasoning in Language Models with Language Models.
NeurIPS
Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman
2023 J jnl
Understanding Social Reasoning in Language Models with Language Models.
CoRR
Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman
2023 A* conf
Why think step by step? Reasoning emerges from the locality of experience.
NeurIPS
Ben Prystawski, Michael Li, Noah D. Goodman
2023 J jnl
Why think step-by-step? Reasoning emerges from the locality of experience.
CoRR
Ben Prystawski, Noah D. Goodman
2022 A* conf
Active Learning Helps Pretrained Models Learn the Intended Task.
NeurIPS
Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
2022 J jnl
Active Learning Helps Pretrained Models Learn the Intended Task.
CoRR
Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
2022 A* conf
Assistive Teaching of Motor Control Tasks to Humans.
NeurIPS
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
2022 J jnl
Assistive Teaching of Motor Control Tasks to Humans.
CoRR
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
2022 B conf
Automated generation of sentence reading fluency test items.
CogSci
Julia White, Amy Burkhardt, Jason D. Yeatman, Noah D. Goodman
2022 A* conf
CLEVRER-Humans: Describing Physical and Causal Events the Human Way.
NeurIPS
Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah D. Goodman, Jiajun Wu
2022 — conf
Causal Distillation for Language Models.
NAACL-HLT
Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman
2022 B conf
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning.
CogSci
Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, Elisa Kreiss
2022 J jnl
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning.
CoRR
Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, Elisa Kreiss
2022 A* conf
Concadia: Towards Image-Based Text Generation with a Purpose.
EMNLP
Elisa Kreiss, Fei Fang, Noah D. Goodman, Christopher Potts
2022 A* conf
DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision.
NeurIPS
Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah D. Goodman
2022 J jnl
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning.
CoRR
Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
2022 J jnl
Flexible social inference facilitates targeted social learning when rewards are not observable.
CoRR
Robert D. Hawkins, Andrew M. Berdahl, Alex 'Sandy' Pentland, Joshua B. Tenenbaum, Noah D. Goodman, P. M. Krafft
2022 A* conf
Foundation Posteriors for Approximate Probabilistic Inference.
NeurIPS
Mike Wu, Noah D. Goodman
2022 J jnl
Foundation Posteriors for Approximate Probabilistic Inference.
CoRR
Mike Wu, Noah D. Goodman
2022 A* conf
Geoclidean: Few-Shot Generalization in Euclidean Geometry.
NeurIPS
Joy Hsu, Jiajun Wu, Noah D. Goodman
2022 J jnl
Geoclidean: Few-Shot Generalization in Euclidean Geometry.
CoRR
Joy Hsu, Jiajun Wu, Noah D. Goodman
2022 A* conf
Improving Intrinsic Exploration with Language Abstractions.
NeurIPS
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
2022 J jnl
Improving Intrinsic Exploration with Language Abstractions.
CoRR
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
2022 A* conf
Inducing Causal Structure for Interpretable Neural Networks.
ICML
Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts
2022 J jnl
Know Thy Student: Interactive Learning with Gaussian Processes.
CoRR
Rose E. Wang, Mike Wu, Noah D. Goodman
2022 J jnl
LEMMA: Bootstrapping High-Level Mathematical Reasoning with Learned Symbolic Abstractions.
CoRR
Zhening Li, Gabriel Poesia, Omar Costilla-Reyes, Noah D. Goodman, Armando Solar-Lezama
2022 A* conf
Language modeling via stochastic processes.
ICLR
Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto
2022 J jnl
Language modeling via stochastic processes.
CoRR
Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto
2022 B conf
Left to the Reader: Abstracting Solutions in Mathematical Reasoning.
CogSci
Gabriel Poesia Reis e Silva, Noah D. Goodman
2022 J jnl
Logic, Probability, and Pragmatics in Syllogistic Reasoning.
Top. Cogn. Sci.
Michael Henry Tessler, Joshua B. Tenenbaum, Noah D. Goodman
2022 A* conf
Mixed-effects transformers for hierarchical adaptation.
EMNLP
Julia White, Noah D. Goodman, Robert X. D. Hawkins
2022 J jnl
Mixed-effects transformers for hierarchical adaptation.
CoRR
Julia White, Noah D. Goodman, Robert X. D. Hawkins
2022 J jnl
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning.
CoRR
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
2022 J jnl
Parsel: A Unified Natural Language Framework for Algorithmic Reasoning.
CoRR
Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber
2022 J jnl
Peano: Learning Formal Mathematical Reasoning.
CoRR
Gabriel Poesia, Noah D. Goodman
2022 J jnl
Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models.
CoRR
Ben Prystawski, Paul H. Thibodeau, Noah D. Goodman
2022 A* conf
STaR: Bootstrapping Reasoning With Reasoning.
NeurIPS
Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman
2022 J jnl
STaR: Bootstrapping Reasoning With Reasoning.
CoRR
Eric Zelikman, Yuhuai Wu, Noah D. Goodman
2022 J jnl
Task Ambiguity in Humans and Language Models.
CoRR
Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman
2022 B conf
Two's company but six is a crowd: emergence of conventions in multiparty communication games.
CogSci
Veronica Boyce, Robert D. Hawkins, Noah D. Goodman, Michael C. Frank
2022 J jnl
Warm (for Winter): Inferring Comparison Classes in Communication.
Cogn. Sci.
Michael Henry Tessler, Noah D. Goodman
2021 J jnl
Applying Probabilistic Programming to Affective Computing.
IEEE Trans. Affect. Comput.
Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman
2021 — conf
Calibrate your listeners! Robust communication-based training for pragmatic speakers.
EMNLP (Findings)
Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
2021 J jnl
Calibrate your listeners! Robust communication-based training for pragmatic speakers.
CoRR
Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
2021 J jnl
Causal Distillation for Language Models.
CoRR
Zhengxuan Wu, Atticus Geiger, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman
2021 J jnl
Concadia: Tackling image accessibility with context.
CoRR
Elisa Kreiss, Noah D. Goodman, Christopher Potts
2021 A* conf
Conditional Negative Sampling for Contrastive Learning of Visual Representations.
ICLR
Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2021 A* conf
Contrastive Reinforcement Learning of Symbolic Reasoning Domains.
NeurIPS
Gabriel Poesia, Wenxin Dong, Noah D. Goodman
2021 J jnl
Contrastive Reinforcement Learning of Symbolic Reasoning Domains.
CoRR
Gabriel Poesia, Wenxin Dong, Noah D. Goodman
2021 J jnl
DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning.
CoRR
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
2021 — conf
DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning.
NeurIPS Datasets and Benchmarks
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
2021 A* conf
Emergent Communication of Generalizations.
NeurIPS
Jesse Mu, Noah D. Goodman
2021 J jnl
Emergent Communication of Generalizations.
CoRR
Jesse Mu, Noah D. Goodman
2021 J jnl
From partners to populations: A hierarchical Bayesian account of coordination and convention.
CoRR
Robert X. D. Hawkins, Michael Franke, Michael C. Frank, Kenny Smith, Thomas L. Griffiths, Noah D. Goodman
2021 B conf
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems.
EDM
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech
2021 A* conf
Improving Compositionality of Neural Networks by Decoding Representations to Inputs.
NeurIPS
Mike Wu, Noah D. Goodman, Stefano Ermon
2021 J jnl
Improving Compositionality of Neural Networks by Decoding Representations to Inputs.
CoRR
Mike Wu, Noah D. Goodman, Stefano Ermon
2021 J jnl
Inducing Causal Structure for Interpretable Neural Networks.
CoRR
Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts
2021 J jnl
Modeling Item Response Theory with Stochastic Variational Inference.
CoRR
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2021 J jnl
Neural Event Semantics for Grounded Language Understanding.
Trans. Assoc. Comput. Linguistics
Shyamal Buch, Li Fei-Fei, Noah D. Goodman
2021 J jnl
On the Opportunities and Risks of Foundation Models.
CoRR
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren E. Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.
2021 — conf
Open-domain clarification question generation without question examples.
EMNLP (1)
Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman
2021 J jnl
Open-domain clarification question generation without question examples.
CoRR
Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman
2021 A* conf
Pragmatic Code Autocomplete.
AAAI
Gabriel Poesia, Noah D. Goodman
2021 J jnl
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback.
CoRR
Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn
2021 — conf
Question Generation for Adaptive Education.
ACL/IJCNLP (2)
Megha Srivastava, Noah D. Goodman
2021 J jnl
Question Generation for Adaptive Education.
CoRR
Megha Srivastava, Noah D. Goodman
2021 J jnl
Temperature as Uncertainty in Contrastive Learning.
CoRR
Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah D. Goodman
2021 J jnl
The Division of Labor in Communication: Speakers Help Listeners Account for Asymmetries in Visual Perspective.
Cogn. Sci.
Robert X. D. Hawkins, Hyowon Gweon, Noah D. Goodman
2021 J jnl
Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study.
CoRR
Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin
2021 A* conf
Viewmaker Networks: Learning Views for Unsupervised Representation Learning.
ICLR
Alex Tamkin, Mike Wu, Noah D. Goodman
2021 J jnl
Visual resemblance and communicative context constrain the emergence of graphical conventions.
CoRR
Robert D. Hawkins, Megumi Sano, Noah D. Goodman, Judith E. Fan
2020 J jnl
A Simple Framework for Uncertainty in Contrastive Learning.
CoRR
Mike Wu, Noah D. Goodman
2020 J jnl
Analyzing Machine-Learned Representations: A Natural Language Case Study.
Cogn. Sci.
Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman
2020 J jnl
Characterizing the Dynamics of Learning in Repeated Reference Games.
Cogn. Sci.
Robert X. D. Hawkins, Michael C. Frank, Noah D. Goodman
2020 J jnl
Conditional Negative Sampling for Contrastive Learning of Visual Representations.
CoRR
Mike Wu, Milan Mossé, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
2020 B conf
Continual Adaptation for Efficient Machine Communication.
CoNLL
Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman
2020 B conf
Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks.
CogSci
Robert X. D. Hawkins, Noah D. Goodman, Adele E. Goldberg, Tom Griffiths
2020 J jnl
Generalizing meanings from partners to populations: Hierarchical inference supports convention formation on networks.
CoRR
Robert X. D. Hawkins, Noah D. Goodman, Adele E. Goldberg, Thomas L. Griffiths
2020 — conf
Investigating Transferability in Pretrained Language Models.
EMNLP (Findings)
Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman
2020 J jnl
Investigating Transferability in Pretrained Language Models.
CoRR
Alex Tamkin, Trisha Singh, Davide Giovanardi, Noah D. Goodman
2020 A* conf
Language Through a Prism: A Spectral Approach for Multiscale Language Representations.
NeurIPS
Alex Tamkin, Dan Jurafsky, Noah D. Goodman
2020 J jnl
Language Through a Prism: A Spectral Approach for Multiscale Language Representations.
CoRR
Alex Tamkin, Dan Jurafsky, Noah D. Goodman
2020 B conf
Learning to refer informatively by amortizing pragmatic reasoning.
CogSci
Julia White, Jesse Mu, Noah D. Goodman
2020 J jnl
Learning to refer informatively by amortizing pragmatic reasoning.
CoRR
Julia White, Jesse Mu, Noah D. Goodman
2020 A* conf
Meta-Amortized Variational Inference and Learning.
AAAI
Mike Wu, Kristy Choi, Noah D. Goodman, Stefano Ermon
2020 J jnl
On Mutual Information in Contrastive Learning for Visual Representations.
CoRR
Mike Wu, Chengxu Zhuang, Milan Mossé, Daniel Yamins, Noah D. Goodman
2020 A* conf
Shaping Visual Representations with Language for Few-Shot Classification.
ACL
Jesse Mu, Percy Liang, Noah D. Goodman
2020 J jnl
The Interactions of Rational, Pragmatic Agents Lead to Efficient Language Structure and Use.
Top. Cogn. Sci.
Benjamin N. Peloquin, Noah D. Goodman, Michael C. Frank
2020 B conf
Variational Item Response Theory: Fast, Accurate, and Expressive.
EDM
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2020 J jnl
Variational Item Response Theory: Fast, Accurate, and Expressive.
CoRR
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
2020 J jnl
Viewmaker Networks: Learning Views for Unsupervised Representation Learning.
CoRR
Alex Tamkin, Mike Wu, Noah D. Goodman
2019 J jnl
Analyzing machine-learned representations: A natural language case study.
CoRR
Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman
2019 J jnl
Applying Probabilistic Programming to Affective Computing.
CoRR
Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman
2019 J jnl
Characterizing the dynamics of learning in repeated reference games.
CoRR
Robert X. D. Hawkins, Michael C. Frank, Noah D. Goodman
2019 J jnl
Computational Models of Emotion Inference in Theory of Mind: A Review and Roadmap.
Top. Cogn. Sci.
Desmond C. Ong, Jamil Zaki, Noah D. Goodman
2019 J jnl
Continual adaptation for efficient machine communication.
CoRR
Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman
2019 A conf
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference.
AISTATS
Mike Wu, Noah D. Goodman, Stefano Ermon
2019 — conf
DisSent: Learning Sentence Representations from Explicit Discourse Relations.
ACL (1)
Allen Nie, Erin Bennett, Noah D. Goodman
2019 B conf
Disentangling contributions of visual information and interaction history in the formation of graphical conventions.
CogSci
Robert X. D. Hawkins, Megumi Sano, Noah D. Goodman, Judith W. Fan
2019 B conf
Extending Rationality.
CogSci
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 J jnl
Generative Grading: Neural Approximate Parsing for Automated Student Feedback.
CoRR
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, John Mitchell, Noah D. Goodman, Chris Piech
2019 — conf
Learning from Omission.
ACL (1)
Bill McDowell, Noah D. Goodman
2019 J jnl
Learning to Explain: Answering Why-Questions via Rephrasing.
CoRR
Allen Nie, Erin D. Bennett, Noah D. Goodman
2019 — conf
Lost in Machine Translation: A Method to Reduce Meaning Loss.
NAACL-HLT (1)
Reuben Cohn-Gordon, Noah D. Goodman
2019 J jnl
Lost in Machine Translation: A Method to Reduce Meaning Loss.
CoRR
Reuben Cohn-Gordon, Noah D. Goodman
2019 J jnl
Meta-Amortized Variational Inference and Learning.
CoRR
Kristy Choi, Mike Wu, Noah D. Goodman, Stefano Ermon
2019 J jnl
Multimodal Generative Models for Compositional Representation Learning.
CoRR
Mike Wu, Noah D. Goodman
2019 J jnl
Pragmatic inference and visual abstraction enable contextual flexibility during visual communication.
CoRR
Judith W. Fan, Robert X. D. Hawkins, Mike Wu, Noah D. Goodman
2019 J jnl
Pyro: Deep Universal Probabilistic Programming.
J. Mach. Learn. Res.
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, Noah D. Goodman
2019 J jnl
ShapeGlot: Learning Language for Shape Differentiation.
CoRR
Panos Achlioptas, Judy Fan, Robert X. D. Hawkins, Noah D. Goodman, Leonidas J. Guibas
2019 A* conf
Shapeglot: Learning Language for Shape Differentiation.
ICCV
Panos Achlioptas, Leonidas J. Guibas, Noah D. Goodman, Judy Fan, Robert X. D. Hawkins
2019 — conf
Shaping Visual Representations with Language for Few-shot Classification.
ViGIL@NeurIPS
Jesse Mu, Percy Liang, Noah D. Goodman
2019 J jnl
Shaping Visual Representations with Language for Few-shot Classification.
CoRR
Jesse Mu, Percy Liang, Noah D. Goodman
2019 A* conf
Tensor Variable Elimination for Plated Factor Graphs.
ICML
Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Neeraj Pradhan, Justin T. Chiu, Alexander M. Rush, Noah D. Goodman
2019 J jnl
Tensor Variable Elimination for Plated Factor Graphs.
CoRR
Fritz Obermeyer, Eli Bingham, Martin Jankowiak, Justin T. Chiu, Neeraj Pradhan, Alexander M. Rush, Noah D. Goodman
2019 B conf
The first crank of the cultural ratchet: Learning and transmitting concepts through language.
CogSci
Sahil Chopra, Michael Henry Tessler, Noah D. Goodman
2019 B conf
The interactions of rational, pragmatic agents lead to efficient language structure and use.
CogSci
Benjamin N. Peloquin, Noah D. Goodman, Michael C. Frank
2019 A* conf
Variational Bayesian Optimal Experimental Design.
NeurIPS
Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah D. Goodman
2019 J jnl
Variational Estimators for Bayesian Optimal Experimental Design.
CoRR
Adam Foster, Martin Jankowiak, Eli Bingham, Paul Horsfall, Yee Whye Teh, Tom Rainforth, Noah D. Goodman
2019 J jnl
When redundancy is rational: A Bayesian approach to 'overinformative' referring expressions.
CoRR
Judith Degen, Robert X. D. Hawkins, Caroline Graf, Elisa Kreiss, Noah D. Goodman
2019 A* conf
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference.
AAAI
Mike Wu, Milan Mossé, Noah D. Goodman, Chris Piech
2018 J jnl
An Incremental Iterated Response Model of Pragmatics.
CoRR
Reuben Cohn-Gordon, Noah D. Goodman, Christopher Potts
2018 B conf
An Information-Theoretic Explanation of Adjective Ordering Preferences.
CogSci
Michael Hahn, Judith Degen, Noah D. Goodman, Dan Jurafsky, Richard Futrell
2018 A* conf
Bias and Generalization in Deep Generative Models: An Empirical Study.
NeurIPS
Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah D. Goodman, Stefano Ermon
2018 J jnl
Bias and Generalization in Deep Generative Models: An Empirical Study.
CoRR
Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah D. Goodman, Stefano Ermon
2018 B conf
Deriving uniform information density behavior in pragmatic agents.
CogSci
Benjamin N. Peloquin, Noah D. Goodman, Michael C. Frank
2018 J jnl
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference.
CoRR
Mike Wu, Noah D. Goodman, Stefano Ermon
2018 B conf
Emerging abstractions: Lexical conventions are shaped by communicative context.
CogSci
Robert X. D. Hawkins, Michael Franke, Kenny Smith, Noah D. Goodman
2018 B conf
Evaluating Compositionality in Sentence Embeddings.
CogSci
Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel Gershman, Noah D. Goodman
2018 J jnl
Evaluating Compositionality in Sentence Embeddings.
CoRR
Ishita Dasgupta, Demi Guo, Andreas Stuhlmüller, Samuel J. Gershman, Noah D. Goodman
2018 B conf
Generalizations, from representation to transmission.
CogSci
Michael Henry Tessler, Noah D. Goodman, David Danks, Emily Foster-Hanson, Marjorie Rhodes, Greg Carlson
2018 J jnl
Joint Mapping and Calibration via Differentiable Sensor Fusion.
CoRR
Jonathan P. Chen, Fritz Obermeyer, Vladimir Lyapunov, Lionel Gueguen, Noah D. Goodman
2018 A* conf
Multimodal Generative Models for Scalable Weakly-Supervised Learning.
NeurIPS
Mike Wu, Noah D. Goodman
2018 J jnl
Multimodal Generative Models for Scalable Weakly-Supervised Learning.
CoRR
Mike Wu, Noah D. Goodman
2018 J jnl
Planning, Inference and Pragmatics in Sequential Language Games.
CoRR
Fereshte Khani, Noah D. Goodman, Percy Liang
2018 J jnl
Planning, Inference, and Pragmatics in Sequential Language Games.
Trans. Assoc. Comput. Linguistics
Fereshte Khani, Noah D. Goodman, Percy Liang
2018 — conf
Pragmatically Informative Image Captioning with Character-Level Inference.
NAACL-HLT (2)
Reuben Cohn-Gordon, Noah D. Goodman, Christopher Potts
2018 J jnl
Pragmatically Informative Image Captioning with Character-Level Reference.
CoRR
Reuben Cohn-Gordon, Noah D. Goodman, Christopher Potts
2018 J jnl
Pyro: Deep Universal Probabilistic Programming.
CoRR
Eli Bingham, Jonathan P. Chen, Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul A. Szerlip, Paul Horsfall, Noah D. Goodman
2018 J jnl
Speakers account for asymmetries in visual perspective so listeners don't have to.
CoRR
Robert X. D. Hawkins, Hyowon Gweon, Noah D. Goodman
2018 B conf
Statistics as Pottery: Bayesian Data Analysis using Probabilistic Programs.
CogSci
Michael Henry Tessler, Noah D. Goodman
2018 J jnl
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference.
CoRR
Mike Wu, Milan Mossé, Noah D. Goodman, Chris Piech
2018 B conf
webppl-oed: A practical optimal experiment design system.
CogSci
Long Ouyang, Michael Henry Tessler, Daniel Ly, Noah D. Goodman
2017 B conf
"I won't lie, it wasn't amazing": Modeling polite indirect speech.
CogSci
Erica J. Yoon, Michael Henry Tessler, Noah D. Goodman, Michael C. Frank
2017 J jnl
Adjectival vagueness in a Bayesian model of interpretation.
Synth.
Daniel Lassiter, Noah D. Goodman
2017 B conf
Amortized Hypothesis Generation.
CogSci
Ishita Dasgupta, Eric Schulz, Noah D. Goodman, Samuel J. Gershman
2017 J jnl
Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding.
CoRR
Will Monroe, Robert X. D. Hawkins, Noah D. Goodman, Christopher Potts
2017 J jnl
Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding.
Trans. Assoc. Comput. Linguistics
Will Monroe, Robert X. D. Hawkins, Noah D. Goodman, Christopher Potts
2017 B conf
Convention-formation in iterated reference games.
CogSci
Robert X. D. Hawkins, Mike Frank, Noah D. Goodman
2017 J jnl
DisSent: Sentence Representation Learning from Explicit Discourse Relations.
CoRR
Allen Nie, Erin D. Bennett, Noah D. Goodman
2017 — conf
Learning Disentangled Representations with Semi-Supervised Deep Generative Models.
NIPS
Siddharth Narayanaswamy, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Noah D. Goodman, Pushmeet Kohli, Frank D. Wood, Philip H. S. Torr
2017 J jnl
Learning Disentangled Representations with Semi-Supervised Deep Generative Models.
CoRR
N. Siddharth, Brooks Paige, Jan-Willem van de Meent, Alban Desmaison, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
2017 B conf
Mentioning atypical properties of objects is communicatively efficient.
CogSci
Elisa Kreiss, Robert X. D. Hawkins, Judith Degen, Noah D. Goodman
2017 B conf
Warm (for winter): Comparison class understanding in vague language.
CogSci
Michael Henry Tessler, Michael Lopez-Brau, Noah D. Goodman
2016 J jnl
A Computational Model of Linguistic Humor in Puns.
Cogn. Sci.
Justine T. Kao, Roger Levy, Noah D. Goodman
2016 J jnl
A pragmatic theory of generic language.
CoRR
Michael Henry Tessler, Noah D. Goodman
2016 B conf
A rational speech-act model of projective content.
CogSci
Ciyang Qing, Noah D. Goodman, Daniel Lassiter
2016 B conf
Animal, dog, or dalmatian? Level of abstraction in nominal referring expressions.
CogSci
Caroline Graf, Judith Degen, Robert X. D. Hawkins, Noah D. Goodman
2016 A conf
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching.
AISTATS
Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman
2016 B conf
Communicating generalizations about events.
CogSci
Michael Henry Tessler, Noah D. Goodman
2016 B conf
Conversational expectations account for apparent limits on theory of mind use.
CogSci
Robert X. D. Hawkins, Noah D. Goodman
2016 J jnl
Deep Amortized Inference for Probabilistic Programs.
CoRR
Daniel Ritchie, Paul Horsfall, Noah D. Goodman
2016 B conf
Emotions in lay explanations of behavior.
CogSci
Desmond C. Ong, Jamil Zaki, Noah D. Goodman
2016 B conf
Empirical and Computational Approaches to Metaphor and Figurative Meaning.
CogSci
Justine T. Kao, Noah D. Goodman
2016 J jnl
Inducing Interpretable Representations with Variational Autoencoders.
CoRR
N. Siddharth, Brooks Paige, Alban Desmaison, Jan-Willem van de Meent, Frank D. Wood, Noah D. Goodman, Pushmeet Kohli, Philip H. S. Torr
2016 A* conf
Learning the Preferences of Ignorant, Inconsistent Agents.
AAAI
Owain Evans, Andreas Stuhlmüller, Noah D. Goodman
2016 A* conf
Learning to Generate Compositional Color Descriptions.
EMNLP
Will Monroe, Noah D. Goodman, Christopher Potts
2016 J jnl
Learning to Generate Compositional Color Descriptions.
CoRR
Will Monroe, Noah D. Goodman, Christopher Potts
2016 — conf
Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks.
NIPS
Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman
2016 J jnl
Neurally-Guided Procedural Models: Learning to Guide Procedural Models with Deep Neural Networks.
CoRR
Daniel Ritchie, Anna Thomas, Pat Hanrahan, Noah D. Goodman
2016 J jnl
Practical optimal experiment design with probabilistic programs.
CoRR
Long Ouyang, Michael Henry Tessler, Daniel Ly, Noah D. Goodman
2016 B conf
Talking with tact: Polite language as a balance between informativity and kindness.
CogSci
Erica J. Yoon, Michael Henry Tessler, Noah D. Goodman, Michael C. Frank
2016 B conf
The Emergence of Conventions.
CogSci
Robert X. D. Hawkins, Noah D. Goodman, Olga Feher, Kenny Smith, Robert L. Goldstone, Tom Griffiths
2016 B conf
The Pragmatics of Spatial Language.
CogSci
Tomer D. Ullman, Yang Xu, Noah D. Goodman
2016 B conf
What does the crowd believe? A hierarchical approach to estimating subjective beliefs from empirical data.
CogSci
Michael Franke, Fabian Dablander, Anthea Schöller, Erin Bennett, Judith Degen, Michael Henry Tessler, Justine T. Kao, Noah D. Goodman
2015 B conf
A Resource-Rational Approach to the Causal Frame Problem.
CogSci
Thomas Icard, Noah D. Goodman
2015 J jnl
C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching.
CoRR
Daniel Ritchie, Andreas Stuhlmüller, Noah D. Goodman
2015 J jnl
Coarse-to-Fine Sequential Monte Carlo for Probabilistic Programs.
CoRR
Andreas Stuhlmüller, Robert X. D. Hawkins, N. Siddharth, Noah D. Goodman
2015 J jnl
Controlling procedural modeling programs with stochastically-ordered sequential Monte Carlo.
ACM Trans. Graph.
Daniel Ritchie, Ben Mildenhall, Noah D. Goodman, Pat Hanrahan
2015 B conf
Emergent Collective Sensing in Human Groups.
CogSci
Peter M. Krafft, Robert X. D. Hawkins, Alex Pentland, Noah D. Goodman, Joshua B. Tenenbaum
2015 B conf
Extremely costly intensifiers are stronger than quite costly ones.
CogSci
Erin Bennett, Noah D. Goodman
2015 J jnl
Generating Design Suggestions under Tight Constraints with Gradient-based Probabilistic Programming.
Comput. Graph. Forum
Daniel Ritchie, Sharon Lin, Noah D. Goodman, Pat Hanrahan
2015 B conf
How, whether, why: Causal judgments as counterfactual contrasts.
CogSci
Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum
2015 J jnl
Learning the Preferences of Ignorant, Inconsistent Agents.
CoRR
Owain Evans, Andreas Stuhlmüller, Noah D. Goodman
2015 B conf
Let's talk (ironically) about the weather: Modeling verbal irony.
CogSci
Justine T. Kao, Noah D. Goodman
2015 B conf
Near-misses sting even when they are uncontrollable.
CogSci
Desmond C. Ong, Noah D. Goodman, Jamil Zaki
2015 B conf
Not by number alone: The effect of teachers' knowledge and its value in evaluating "sins of omission".
CogSci
Ilona Bass, Daniel Hawthorne, Noah D. Goodman, Hyowon Gweon
2015 J jnl
Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic.
Top. Cogn. Sci.
Thomas L. Griffiths, Falk Lieder, Noah D. Goodman
2015 B conf
So good it has to be true: Wishful thinking in theory of mind.
CogSci
Daniel Hawthorne-Madell, Noah D. Goodman
2015 J jnl
The Strategic Use of Noise in Pragmatic Reasoning.
Top. Cogn. Sci.
Leon Bergen, Noah D. Goodman
2015 B conf
Toddlers Always Get the Last Word: Recency biases in early verbal behavior.
CogSci
Emily Sumner, Erika DeAngelis, Mara Hyatt, Noah D. Goodman, Celeste Kidd
2015 B conf
Why do you ask? Good questions provoke informative answers.
CogSci
Robert X. D. Hawkins, Andreas Stuhlmüller, Judith Degen, Noah D. Goodman
2015 B conf
Wonky worlds: Listeners revise world knowledge when utterances are odd.
CogSci
Judith Degen, Michael Henry Tessler, Noah D. Goodman
2014 B conf
Amortized Inference in Probabilistic Reasoning.
CogSci
Samuel Gershman, Noah D. Goodman
2014 B conf
Formalizing the Pragmatics of Metaphor Understanding.
CogSci
Justine T. Kao, Leon Bergen, Noah D. Goodman
2014 B conf
From counterfactual simulation to causal judgment.
CogSci
Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum
2014 A conf
Generating Efficient MCMC Kernels from Probabilistic Programs.
AISTATS
Lingfeng Yang, Pat Hanrahan, Noah D. Goodman
2014 B conf
Learning physical theories from dynamical scenes.
CogSci
Tomer D. Ullman, Andreas Stuhlmüller, Noah D. Goodman, Joshua B. Tenenbaum
2014 B conf
Lost your marbles? The puzzle of dependent measures in experimental pragmatics.
CogSci
Judith Degen, Noah D. Goodman
2014 J jnl
One and Done? Optimal Decisions From Very Few Samples.
Cogn. Sci.
Edward Vul, Noah D. Goodman, Thomas L. Griffiths, Joshua B. Tenenbaum
2014 B conf
Probability, programs, and the mind: Building structured Bayesian models of cognition.
CogSci
Noah D. Goodman, Joshua B. Tenenbaum
2014 J jnl
Reasoning about reasoning by nested conditioning: Modeling theory of mind with probabilistic programs.
Cogn. Syst. Res.
Andreas Stuhlmüller, Noah D. Goodman
2014 B conf
Some arguments are probably valid: Syllogistic reasoning as communication.
CogSci
Michael Henry Tessler, Noah D. Goodman
2014 B conf
Symposium: The Role of Alternatives in Pragmatic Inference.
CogSci
Judith Degen, Noah D. Goodman, Roni Katzir, David Barner, Albert Gatt
2014 B conf
The strategic use of noise in pragmatic reasoning.
CogSci
Leon Bergen, Noah D. Goodman
2014 B conf
Understanding Affective Cognition: Frontiers in modeling reasoning about others' emotions.
CogSci
Desmond C. Ong, Jamil Zaki, Noah D. Goodman
2013 J jnl
Knowledge and Implicature: Modeling Language Understanding as Social Cognition.
Top. Cogn. Sci.
Noah D. Goodman, Andreas Stuhlmüller
2013 B conf
Learned helplessness and generalization.
CogSci
Falk Lieder, Noah D. Goodman, Quentin J. M. Huys
2013 — conf
Learning Stochastic Inverses.
NIPS
Andreas Stuhlmüller, Jessica Taylor, Noah D. Goodman
2013 — conf
Learning and using language via recursive pragmatic reasoning about other agents.
NIPS
Nathaniel J. Smith, Noah D. Goodman, Michael C. Frank
2013 B conf
Minimal Nativism: How does cognitive development get off the ground?
CogSci
Tomer D. Ullman, Joshua B. Tenenbaum, Noah D. Goodman, Shimon Ullman, Elizabeth S. Spelke
2013 B conf
The Funny Thing About Incongruity: A Computational Model of Humor in Puns.
CogSci
Justine T. Kao, Roger Levy, Noah D. Goodman
2013 A* conf
The principles and practice of probabilistic programming.
POPL
Noah D. Goodman
2012 — conf
"Burn-in, bias, and the rationality of anchoring".
NIPS
Falk Lieder, Thomas L. Griffiths, Noah D. Goodman
2012 J jnl
A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs
CoRR
Andreas Stuhlmüller, Noah D. Goodman
2012 — conf
A Dynamic Programming Algorithm for Inference in Recursive Probabilistic Programs.
StarAI@UAI
Andreas Stuhlmüller, Noah D. Goodman
2012 J jnl
Church: a language for generative models
CoRR
Noah D. Goodman, Vikash Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum
2012 B conf
How many kinds of reasoning? Inference, probability, and natural language semantics.
CogSci
Daniel Lassiter, Noah D. Goodman
2012 B conf
Knowledge and implicature: Modeling language understanding as social cognition.
CogSci
Noah D. Goodman, Andreas Stuhlmüller
2012 A* conf
Learning design patterns with bayesian grammar induction.
UIST
Jerry O. Talton, Lingfeng Yang, Ranjitha Kumar, Maxine Lim, Noah D. Goodman, Radomír Mech
2012 B conf
Noisy Newtons: Unifying process and dependency accounts of causal attribution.
CogSci
Tobias Gerstenberg, Noah D. Goodman, David A. Lagnado, Joshua B. Tenenbaum
2012 B conf
Ping Pong in Church: Productive use of concepts in human probabilistic inference.
CogSci
Tobias Gerstenberg, Noah D. Goodman
2012 B conf
Probability, programs, and the mind: Building structured Bayesian models of cognition.
CogSci
Noah D. Goodman, Joshua B. Tenenbaum
2012 J jnl
Synthesizing open worlds with constraints using locally annealed reversible jump MCMC.
ACM Trans. Graph.
Yi-Ting Yeh, Lingfeng Yang, Matthew Watson, Noah D. Goodman, Pat Hanrahan
2012 B conf
That's what she (could have) said: How alternative utterances affect language use.
CogSci
Leon Bergen, Noah D. Goodman, Roger Levy
2012 J jnl
The Infinite Latent Events Model
CoRR
David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
2011 B conf
Ad-hoc scalar implicature in adults and children.
CogSci
Alex Stiller, Noah D. Goodman, Michael C. Frank
2011 A* conf
Bayesian Policy Search with Policy Priors.
IJCAI
David Wingate, Noah D. Goodman, Daniel M. Roy, Leslie Pack Kaelbling, Joshua B. Tenenbaum
2011 B conf
Forward Physics: How people learn and generalize novel dynamical models.
CogSci
Tomer D. Ullman, Noah D. Goodman, Josh Tenenbaum
2011 J jnl
Inducing Probabilistic Programs by Bayesian Program Merging
CoRR
Irvin Hwang, Andreas Stuhlmüller, Noah D. Goodman
2011 — conf
Learning and the language of thought.
ICCV Workshops
Noah D. Goodman
2011 A conf
Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation.
AISTATS
David Wingate, Andreas Stuhlmüller, Noah D. Goodman
2011 — conf
Nonstandard Interpretations of Probabilistic Programs for Efficient Inference.
NIPS
David Wingate, Noah D. Goodman, Andreas Stuhlmüller, Jeffrey Mark Siskind
2011 B conf
Productivity and Reuse in Language.
CogSci
Timothy J. O'Donnell, Jesse Snedeker, Joshua B. Tenenbaum, Noah D. Goodman
2011 B conf
Productivity and Reuse in Language: a Developmental Study.
CogSci
Timothy J. O'Donnell, Jesse Snedeker, Joshua B. Tenenbaum, Noah D. Goodman
2010 J jnl
Learning to Learn Causal Models.
Cogn. Sci.
Charles Kemp, Noah D. Goodman, Joshua B. Tenenbaum
2009 — conf
Help or Hinder: Bayesian Models of Social Goal Inference.
NIPS
Tomer D. Ullman, Chris L. Baker, Owen Macindoe, Owain Evans, Noah D. Goodman, Joshua B. Tenenbaum
2009 A conf
The Infinite Latent Events Model.
UAI
David Wingate, Noah D. Goodman, Daniel M. Roy, Joshua B. Tenenbaum
2008 — conf
A Bayesian Model of Pedagogical Reasoning.
AAAI Fall Symposium: Naturally-Inspired Artificial Intelligence
Patrick Shafto, Noah D. Goodman
2008 J jnl
A Rational Analysis of Rule-Based Concept Learning.
Cogn. Sci.
Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldman, Thomas L. Griffiths
2008 A conf
Church: a language for generative models.
UAI
Noah D. Goodman, Vikash K. Mansinghka, Daniel M. Roy, Kallista A. Bonawitz, Joshua B. Tenenbaum
2007 — conf
A Bayesian Framework for Cross-Situational Word-Learning.
NIPS
Michael C. Frank, Noah D. Goodman, Joshua B. Tenenbaum
2007 — conf
Learning and using relational theories.
NIPS
Charles Kemp, Noah D. Goodman, Joshua B. Tenenbaum