Noah D. Goodman

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 216

Top Venues

CoRR

CogSci

NeurIPS

Cogn. Sci.

Publications

Zhengxuan Wu, Atticus Geiger, Jing Huang, Aryaman Arora, Thomas Icard, Christopher Potts, Noah D. Goodman
A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments. CoRR (2024)
Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
Multispectral Self-Supervised Learning with Viewmaker Networks. CoRR (2023)
Zhengxuan Wu, Atticus Geiger, Thomas Icard, Christopher Potts, Noah D. Goodman
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca. NeurIPS (2023)
Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah D. Goodman, Jiajun Wu
CLEVRER-Humans: Describing Physical and Causal Events the Human Way. CoRR (2023)
Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber
Parsel🦆: Algorithmic Reasoning with Language Models by Composing Decompositions. NeurIPS (2023)
Megha Srivastava, Noah D. Goodman, Dorsa Sadigh
Generating Language Corrections for Teaching Physical Control Tasks. CoRR (2023)
Joy He-Yueya, Gabriel Poesia, Rose E. Wang, Noah D. Goodman
Solving Math Word Problems by Combining Language Models With Symbolic Solvers. CoRR (2023)
Zhengxuan Wu, Atticus Geiger, Christopher Potts, Noah D. Goodman
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca. CoRR (2023)
Eric Zelikman, Qian Huang, Percy Liang, Nick Haber, Noah D. Goodman
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness. CoRR (2023)
Jesse Mu, Xiang Lisa Li, Noah D. Goodman
Learning to Compress Prompts with Gist Tokens. CoRR (2023)
Ben Prystawski, Noah D. Goodman
Why think step-by-step? Reasoning emerges from the locality of experience. CoRR (2023)
Atticus Geiger, Zhengxuan Wu, Christopher Potts, Thomas Icard, Noah D. Goodman
Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations. CoRR (2023)
Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. NeurIPS (2023)
Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman
Strategic Reasoning with Language Models. CoRR (2023)
Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman
Understanding Social Reasoning in Language Models with Language Models. NeurIPS (2023)
Rose E. Wang, Pawan Wirawarn, Noah D. Goodman, Dorottya Demszky
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts. CoRR (2023)
Megha Srivastava, Noah D. Goodman, Dorsa Sadigh
Generating Language Corrections for Teaching Physical Control Tasks. ICML (2023)
Polina Tsvilodub, Michael Franke, Robert D. Hawkins, Noah D. Goodman
Overinformative Question Answering by Humans and Machines. CoRR (2023)
Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas
Eliciting Human Preferences with Language Models. CoRR (2023)
Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman
Hypothesis Search: Inductive Reasoning with Language Models. CoRR (2023)
Jan-Philipp Fränken, Sam Kwok, Peixuan Ye, Kanishk Gandhi, Dilip Arumugam, Jared Moore, Alex Tamkin, Tobias Gerstenberg, Noah D. Goodman
Social Contract AI: Aligning AI Assistants with Implicit Group Norms. CoRR (2023)
Jasmine Bayrooti, Noah D. Goodman, Alex Tamkin
Multispectral Contrastive Learning with Viewmaker Networks. CVPR Workshops (2023)
Alex Tamkin, Mohammad Taufeeque, Noah D. Goodman
Codebook Features: Sparse and Discrete Interpretability for Neural Networks. CoRR (2023)
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
Bayesian Reinforcement Learning with Limited Cognitive Load. CoRR (2023)
Lionel Wong, Gabriel Grand, Alexander K. Lew, Noah D. Goodman, Vikash K. Mansinghka, Jacob Andreas, Joshua B. Tenenbaum
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought. CoRR (2023)
Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman
Certified Reasoning with Language Models. CoRR (2023)
Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman
Understanding Social Reasoning in Language Models with Language Models. CoRR (2023)
Jesse Mu, Xiang Li, Noah D. Goodman
Learning to Compress Prompts with Gist Tokens. NeurIPS (2023)
Alex Tamkin, Kunal Handa, Avash Shrestha, Noah D. Goodman
Task Ambiguity in Humans and Language Models. ICLR (2023)
Rose E. Wang, Pawan Wirawarn, Noah D. Goodman, Dorottya Demszky
SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts. BEA@ACL (2023)
Dhara Yu, Noah D. Goodman, Jesse Mu
Characterizing tradeoffs between teaching via language and demonstrations in multi-agent systems. CoRR (2023)
Fei Fang, Kunal Sinha, Noah D. Goodman, Christopher Potts, Elisa Kreiss
Color Overmodification Emerges from Data-Driven Learning and Pragmatic Reasoning. CoRR (2022)
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
Assistive Teaching of Motor Control Tasks to Humans. NeurIPS (2022)
Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
Active Learning Helps Pretrained Models Learn the Intended Task. NeurIPS (2022)
Alex Tamkin, Dat Nguyen, Salil Deshpande, Jesse Mu, Noah D. Goodman
Active Learning Helps Pretrained Models Learn the Intended Task. CoRR (2022)
Robert D. Hawkins, Andrew M. Berdahl, Alex 'Sandy' Pentland, Joshua B. Tenenbaum, Noah D. Goodman, P. M. Krafft
Flexible social inference facilitates targeted social learning when rewards are not observable. CoRR (2022)
Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman
STaR: Bootstrapping Reasoning With Reasoning. NeurIPS (2022)
Zhengxuan Wu, Atticus Geiger, Joshua Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman
Causal Distillation for Language Models. NAACL-HLT (2022)
Dilip Arumugam, Mark K. Ho, Noah D. Goodman, Benjamin Van Roy
On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning. CoRR (2022)
Jiayuan Mao, Xuelin Yang, Xikun Zhang, Noah D. Goodman, Jiajun Wu
CLEVRER-Humans: Describing Physical and Causal Events the Human Way. NeurIPS (2022)
Rose E. Wang, Mike Wu, Noah D. Goodman
Know Thy Student: Interactive Learning with Gaussian Processes. CoRR (2022)
Joy Hsu, Jiajun Wu, Noah D. Goodman
Geoclidean: Few-Shot Generalization in Euclidean Geometry. CoRR (2022)
Eric Zelikman, Yuhuai Wu, Noah D. Goodman
STaR: Bootstrapping Reasoning With Reasoning. CoRR (2022)
Elisa Kreiss, Fei Fang, Noah D. Goodman, Christopher Potts
Concadia: Towards Image-Based Text Generation with a Purpose. EMNLP (2022)
Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber
Parsel: A Unified Natural Language Framework for Algorithmic Reasoning. CoRR (2022)
Mike Wu, Noah D. Goodman
Foundation Posteriors for Approximate Probabilistic Inference. NeurIPS (2022)
Ben Prystawski, Paul H. Thibodeau, Noah D. Goodman
Psychologically-informed chain-of-thought prompts for metaphor understanding in large language models. CoRR (2022)
Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts
Inducing Causal Structure for Interpretable Neural Networks. ICML (2022)
Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto
Language modeling via stochastic processes. ICLR (2022)
Joy Hsu, Jiajun Wu, Noah D. Goodman
Geoclidean: Few-Shot Generalization in Euclidean Geometry. NeurIPS (2022)
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
Improving Intrinsic Exploration with Language Abstractions. NeurIPS (2022)
Zhening Li, Gabriel Poesia, Omar Costilla-Reyes, Noah D. Goodman, Armando Solar-Lezama
LEMMA: Bootstrapping High-Level Mathematical Reasoning with Learned Symbolic Abstractions. CoRR (2022)
Alex Tamkin, Gaurab Banerjee, Mohamed Owda, Vincent Liu, Shashank Rammoorthy, Noah D. Goodman
DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision. NeurIPS (2022)
Julia White, Noah D. Goodman, Robert X. D. Hawkins
Mixed-effects transformers for hierarchical adaptation. CoRR (2022)
Gabriel Poesia, Noah D. Goodman
Peano: Learning Formal Mathematical Reasoning. CoRR (2022)
Rose E. Wang, Esin Durmus, Noah D. Goodman, Tatsunori Hashimoto
Language modeling via stochastic processes. CoRR (2022)
Michael Henry Tessler, Joshua B. Tenenbaum, Noah D. Goodman
Logic, Probability, and Pragmatics in Syllogistic Reasoning. Top. Cogn. Sci. 14 (3) (2022)
Jesse Mu, Victor Zhong, Roberta Raileanu, Minqi Jiang, Noah D. Goodman, Tim Rocktäschel, Edward Grefenstette
Improving Intrinsic Exploration with Language Abstractions. CoRR (2022)
Alex Tamkin, Margalit Glasgow, Xiluo He, Noah D. Goodman
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning. CoRR (2022)
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
Assistive Teaching of Motor Control Tasks to Humans. CoRR (2022)
Mike Wu, Noah D. Goodman
Foundation Posteriors for Approximate Probabilistic Inference. CoRR (2022)
Julia White, Noah D. Goodman, Robert X. D. Hawkins
Mixed-effects transformers for hierarchical adaptation. EMNLP (2022)
Michael Henry Tessler, Noah D. Goodman
Warm (for Winter): Inferring Comparison Classes in Communication. Cogn. Sci. 46 (3) (2022)
Gabriel Poesia, Wenxin Dong, Noah D. Goodman
Contrastive Reinforcement Learning of Symbolic Reasoning Domains. NeurIPS (2021)
Mike Wu, Noah D. Goodman, Stefano Ermon
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. CoRR (2021)
Gabriel Poesia, Noah D. Goodman
Pragmatic Code Autocomplete. AAAI (2021)
Zhengxuan Wu, Atticus Geiger, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D. Goodman
Causal Distillation for Language Models. CoRR (2021)
Robert X. D. Hawkins, Hyowon Gweon, Noah D. Goodman
The Division of Labor in Communication: Speakers Help Listeners Account for Asymmetries in Visual Perspective. Cogn. Sci. 45 (3) (2021)
Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman
Open-domain clarification question generation without question examples. EMNLP (1) (2021)
Mike Wu, Noah D. Goodman, Chris Piech, Chelsea Finn
ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback. CoRR (2021)
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ 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 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.
On the Opportunities and Risks of Foundation Models. CoRR (2021)
Jesse Mu, Noah D. Goodman
Emergent Communication of Generalizations. CoRR (2021)
Robert X. D. Hawkins, Michael Franke, Michael C. Frank, Kenny Smith, Thomas L. Griffiths, Noah D. Goodman
From partners to populations: A hierarchical Bayesian account of coordination and convention. CoRR (2021)
Gabriel Poesia, Wenxin Dong, Noah D. Goodman
Contrastive Reinforcement Learning of Symbolic Reasoning Domains. CoRR (2021)
Mike Wu, Milan Mosse, Chengxu Zhuang, Daniel Yamins, Noah D. Goodman
Conditional Negative Sampling for Contrastive Learning of Visual Representations. ICLR (2021)
Shyamal Buch, Li Fei-Fei, Noah D. Goodman
Neural Event Semantics for Grounded Language Understanding. Trans. Assoc. Comput. Linguistics 9 (2021)
Elisa Kreiss, Noah D. Goodman, Christopher Potts
Concadia: Tackling image accessibility with context. CoRR (2021)
Megha Srivastava, Noah D. Goodman
Question Generation for Adaptive Education. ACL/IJCNLP (2) (2021)
Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
Calibrate your listeners! Robust communication-based training for pragmatic speakers. CoRR (2021)
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
DABS: a Domain-Agnostic Benchmark for Self-Supervised Learning. NeurIPS Datasets and Benchmarks (2021)
Alex Tamkin, Mike Wu, Noah D. Goodman
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. ICLR (2021)
Atticus Geiger, Zhengxuan Wu, Hanson Lu, Josh Rozner, Elisa Kreiss, Thomas Icard, Noah D. Goodman, Christopher Potts
Inducing Causal Structure for Interpretable Neural Networks. CoRR (2021)
Alex Tamkin, Vincent Liu, Rongfei Lu, Daniel Fein, Colin Schultz, Noah D. Goodman
DABS: A Domain-Agnostic Benchmark for Self-Supervised Learning. CoRR (2021)
Jesse Mu, Noah D. Goodman
Emergent Communication of Generalizations. NeurIPS (2021)
Oliver Zhang, Mike Wu, Jasmine Bayrooti, Noah D. Goodman
Temperature as Uncertainty in Contrastive Learning. CoRR (2021)
Ali Malik, Mike Wu, Vrinda Vasavada, Jinpeng Song, Madison Coots, John Mitchell, Noah D. Goodman, Chris Piech
Generative Grading: Near Human-level Accuracy for Automated Feedback on Richly Structured Problems. EDM (2021)
Megha Srivastava, Noah D. Goodman
Question Generation for Adaptive Education. CoRR (2021)
Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman
Open-domain clarification question generation without question examples. CoRR (2021)
Mike Wu, Richard Lee Davis, Benjamin W. Domingue, Chris Piech, Noah D. Goodman
Modeling Item Response Theory with Stochastic Variational Inference. CoRR (2021)
Desmond C. Ong, Harold Soh, Jamil Zaki, Noah D. Goodman
Applying Probabilistic Programming to Affective Computing. IEEE Trans. Affect. Comput. 12 (2) (2021)
Mike Wu, Noah D. Goodman, Stefano Ermon
Improving Compositionality of Neural Networks by Decoding Representations to Inputs. NeurIPS (2021)
Robert D. Hawkins, Megumi Sano, Noah D. Goodman, Judith E. Fan
Visual resemblance and communicative context constrain the emergence of graphical conventions. CoRR (2021)
Ananya Karthik, Mike Wu, Noah D. Goodman, Alex Tamkin
Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study. CoRR (2021)
Rose E. Wang, Julia White, Jesse Mu, Noah D. Goodman
Calibrate your listeners! Robust communication-based training for pragmatic speakers. EMNLP (Findings) (2021)
Alex Tamkin, Dan Jurafsky, Noah D. Goodman
Language Through a Prism: A Spectral Approach for Multiscale Language Representations. CoRR (2020)
Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman
Continual Adaptation for Efficient Machine Communication. CoNLL (2020)
Alex Tamkin, Mike Wu, Noah D. Goodman
Viewmaker Networks: Learning Views for Unsupervised Representation Learning. CoRR (2020)
Jesse Mu, Percy Liang, Noah D. Goodman
Shaping Visual Representations with Language for Few-Shot Classification. ACL (2020)
Ishita Dasgupta, Demi Guo, Samuel J. Gershman, Noah D. Goodman
Analyzing Machine-Learned Representations: A Natural Language Case Study. Cogn. Sci. 44 (12) (2020)
Robert X. D. Hawkins, Michael C. Frank, Noah D. Goodman
Characterizing the Dynamics of Learning in Repeated Reference Games. Cogn. Sci. 44 (6) (2020)

Noah D. Goodman.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Noah D. Goodman