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Noah D. Goodman

  1. On the Opportunities and Risks of Foundation Models
    2021/08/16 by Rishi Bommasani, Drew A. Hudson, Bommasani, Rishi +233 · 11 voices · 542 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #Adversarial Robustness in Machine Learning #Topic Modeling
  2. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs
    2025/03/03 by Kanishk Gandhi, Ayush Chakravarthy, Gandhi, Kanishk +7 · 22 voices · 125 citations
    #cs.CL #cs.LG
  3. Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
    2024/03/14 by Eric Zelikman, Zelikman, Eric, Georges Harik +9 · 8 voices · 55 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling
  4. Pyro: Deep Universal Probabilistic Programming
    2018/10/18 by Eli Bingham, Bingham, Eli, Jonathan P. Chen +17 · 1 voice · 63 citations
    Computer Science · Mathematics · #Computational Physics and Python Applications #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Programming Languages (cs.PL) #cs.LG #cs.PL #stat.ML
  5. From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought
    2023/06/22 by Lionel Wong, Gabriel Grand, Wong, Lionel +11 · 2 voices · 17 citations
    #cs.CL #cs.AI #cs.SC
  6. Stream of Search (SoS): Learning to Search in Language
    2024/04/01 by Kanishk Gandhi, Gandhi, Kanishk, Denise Lee +11 · 3 voices · 20 citations
    Computer Science · #Speech and dialogue systems #cs.AI #cs.CL #cs.LG
  7. Learning to Compress Prompts with Gist Tokens
    2023/04/17 by Jesse Mu, Mu, Jesse, Xiang Lisa Li +3 · 40 citations
    Computer Science · Engineering · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Natural Language Processing Techniques #Topic Modeling
  8. Multimodal Generative Models for Scalable Weakly-Supervised Learning
    2018/02/14 by Mike Wu, Wu, Mike, Noah D. Goodman +1 · 21 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications
  9. Understanding Social Reasoning in Language Models with Language Models
    2023/06/21 by Kanishk Gandhi, Jan-Philipp Fränken, Gandhi, Kanishk +5 · 24 citations
    Computer Science · Social Sciences · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computational and Text Analysis Methods #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Topic Modeling
  10. Hypothesis Search: Inductive Reasoning with Language Models
    2023/09/11 by Ruocheng Wang, Eric Zelikman, Wang, Ruocheng +9 · 21 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Software Engineering Research
  11. Finding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
    2023/03/05 by Atticus Geiger, Zhengxuan Wu, Geiger, Atticus +7 · 18 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Adversarial Robustness in Machine Learning #Bayesian Modeling and Causal Inference
  12. Learning Disentangled Representations with Semi-Supervised Deep Generative Models
    2017/06/01 by Brooks Paige, Siddharth, N., Paige, Brooks +12 · 12 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  13. STaR-GATE: Teaching Language Models to Ask Clarifying Questions
    2024/03/28 by Chinmaya Andukuri, Jan-Philipp Fränken, Andukuri, Chinmaya +5 · 15 citations
    Computer Science · #Natural Language Processing Techniques #Topic Modeling
  14. Solving Math Word Problems by Combining Language Models With Symbolic Solvers
    2023/04/16 by Joy He-Yueya, He-Yueya, Joy, Gabriel Poesia +5 · 11 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
  15. Variational Bayesian Optimal Experimental Design
    2019/03/13 by Adam Foster, Foster, Adam, Martin Jankowiak +11 · 7 citations
    Decision Sciences · Computer Science · #Optimal Experimental Design Methods #Advanced Multi-Objective Optimization Algorithms #Probabilistic and Robust Engineering Design
  16. On scalable oversight with weak LLMs judging strong LLMs
    2024/07/05 by Zachary Kenton, Kenton, Zachary, Noah Y. Siegel +19 · 1 voice · 13 citations
    Computer Science · Decision Sciences · Social Sciences · #Multi-Agent Systems and Negotiation #Auction Theory and Applications #Access Control and Trust
  17. From partners to populations: A hierarchical Bayesian account of coordination and convention
    2021/04/12 by Robert D. Hawkins, Michael Franke, Hawkins, Robert D. +12 · 1 voice · 5 citations
    Computer Science · Social Sciences · #Language and cultural evolution #Natural Language Processing Techniques #Speech and dialogue systems #cs.AI #cs.CL
  18. On Mutual Information in Contrastive Learning for Visual Representations
    2020/05/27 by Mike Wu, Wu, Mike, Chengxu Zhuang +7 · 10 citations
    Computer Science · #Advanced Image and Video Retrieval Techniques #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
  19. Inducing Causal Structure for Interpretable Neural Networks
    2021/12/01 by Atticus Geiger, Geiger, Atticus, Zhengxuan Wu +13 · 5 citations
    Computer Science · #Explainable Artificial Intelligence (XAI) #Topic Modeling #Bayesian Modeling and Causal Inference
  20. Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
    2023/05/15 by Zhengxuan Wu, Atticus Geiger, Wu, Zhengxuan +6 · 7 citations
    Computer Science · #Adversarial Robustness in Machine Learning #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Topic Modeling
  21. The anchoring bias reflects rational use of cognitive resources
    2017/05/08 by Falk Lieder, Thomas L. Griffiths, Quentin J. M. Huys +1 · 5 citations
    Decision Sciences · Neuroscience · Psychology · #Child and Animal Learning Development #Decision-Making and Behavioral Economics #Neural and Behavioral Psychology Studies
  22. Learning Formal Mathematics From Intrinsic Motivation
    2024/06/30 by Gabriel Poesia, Poesia, Gabriel, David Broman +5 · 1 voice · 7 citations
    Computer Science · Mathematics · Social Sciences · #Computability, Logic, AI Algorithms #History and Theory of Mathematics #Mathematics Education and Teaching Techniques #cs.AI #cs.LO
  23. pyvene: A Library for Understanding and Improving PyTorch Models via Interventions
    2024/03/12 by Zhengxuan Wu, Atticus Geiger, Wu, Zhengxuan +13 · 7 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Software System Performance and Reliability
  24. Language Through a Prism: A Spectral Approach for Multiscale Language Representations
    2020/11/09 by Alex Tamkin, Tamkin, Alex, Dan Jurafsky +3 · 3 citations
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Speech Recognition and Synthesis
  25. Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models
    2024/07/22 by Joy He-Yueya, Wanjing Anya, He-Yueya, Joy +9 · 5 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #Online Learning and Analytics #Topic Modeling
  26. Multimodal Generative Models for Compositional Representation Learning
    2019/12/11 by Mike Wu, Noah D. Goodman, Wu, Mike +1 · 2 citations
    Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications #Topic Modeling
  27. Is Child-Directed Speech Effective Training Data for Language Models?
    2024/08/07 by Steven Y. Feng, Feng, Steven Y., Noah D. Goodman +3 · 4 citations
    Computer Science · #Speech Recognition and Synthesis #Natural Language Processing Techniques #Topic Modeling
  28. What Makes a Maze Look Like a Maze?
    2024/09/12 by Joy Hsu, Hsu, Joy, Jiayuan Mao +7 · 5 citations
    Arts and Humanities · Engineering · Psychology · #Architecture and Computational Design #Architecture and Cultural Influences #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Jungian Analytical Psychology #Machine Learning (cs.LG)
  29. Theory learning as stochastic search in the language of thought
    2012/08/04 by Tomer Ullman, Tomer D. Ullman, Noah D. Goodman +1 · 3 citations
    Computer Science · Psychology · Social Sciences · #Child and Animal Learning Development #Evolutionary Algorithms and Applications #Language and cultural evolution
  30. Bayesian scaling laws for in-context learning
    2024/10/21 by Aryaman Arora, Dan Jurafsky, Arora, Aryaman +5 · 4 citations
    Computer Science · #Anomaly Detection Techniques and Applications #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Formal Languages and Automata Theory (cs.FL) #I.2.7 #Machine Learning (cs.LG)
  31. In-Context Learning Strategies Emerge Rationally
    2025/06/21 by Daniel Wurgaft, Wurgaft, Daniel, Ekdeep Singh Lubana +9 · 2 voices · 5 citations
    #cs.LG #cs.AI
  32. A Reply to Makelov et al. (2023)'s "Interpretability Illusion" Arguments
    2024/01/23 by Zhengxuan Wu, Wu, Zhengxuan, Atticus Geiger +11 · 1 voice · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.AI #cs.CL #cs.LG
  33. C3: Lightweight Incrementalized MCMC for Probabilistic Programs using Continuations and Callsite Caching
    2015/09/07 by Daniel Ritchie, Andreas Stuhlmüller, Ritchie, Daniel +3 · 1 citation
    Computer Science · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Formal Methods in Verification #Parallel Computing and Optimization Techniques #Programming Languages (cs.PL)
  34. Practical optimal experiment design with probabilistic programs
    2016/08/17 by Long Ouyang, Michael Tessler, Ouyang, Long +5 · 1 citation
    Computer Science · Mathematics · #Advanced Multi-Objective Optimization Algorithms #Artificial Intelligence (cs.AI) #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Statistics Education and Methodologies
  35. Learning the Preferences of Ignorant, Inconsistent Agents
    2015/12/18 by Owain Evans, Evans, Owain, Andreas Stuhlmueller +3 · 1 citation
    Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #Complex Systems and Decision Making #Decision-Making and Behavioral Economics #FOS: Computer and information sciences
  36. Tensor Variable Elimination for Plated Factor Graphs
    2019/02/08 by Fritz Obermeyer, Eli Bingham, Obermeyer, Fritz +11 · 1 citation
    Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Tensor decomposition and applications
  37. Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels
    2024/04/22 by Jan-Philipp Fränken, Eric Zelikman, Fränken, Jan-Philipp +9 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques
  38. Learning to refer informatively by amortizing pragmatic reasoning
    2020/05/31 by Julia White, White, Julia, Jesse Mu +3 · 1 citation
    Computer Science · #Topic Modeling #Natural Language Processing Techniques #Speech and dialogue systems
  39. Conditional Negative Sampling for Contrastive Learning of Visual Representations
    2020/10/05 by Mike Wu, Wu, Mike, Milan Mosse +7 · 1 citation
    Computer Science · #Advanced Image and Video Retrieval Techniques #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multimodal Machine Learning Applications
  40. Viewmaker Networks: Learning Views for Unsupervised Representation Learning
    2020/10/14 by Alex Tamkin, Mike Wu, Tamkin, Alex +3 · 1 citation
    Computer Science · #Adversarial Robustness in Machine Learning #Computation and Language (cs.CL) #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multimodal Machine Learning Applications
  41. Bayesian Reinforcement Learning with Limited Cognitive Load
    2023/05/05 by Dilip Arumugam, Mark K. Ho, Arumugam, Dilip +5 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Evolutionary Algorithms and Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
  42. Tradeoffs Between Contrastive and Supervised Learning: An Empirical Study
    2021/12/10 by A. Vijay Karthik, Mike Wu, Karthik, Ananya +5 · 1 citation
    Computer Science · Engineering · #Computer Vision and Pattern Recognition (cs.CV) #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Remote-Sensing Image Classification
  43. Belief Dynamics Reveal the Dual Nature of In-Context Learning and Activation Steering
    2025/11/01 by Eric Bigelow, Bigelow, Eric, Daniel Wurgaft +12 · 1 voice · 3 citations
    Computer Science · Neuroscience · #Topic Modeling #Explainable Artificial Intelligence (XAI) #Embodied and Extended Cognition
  44. Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
    2022/12/16 by Alex Tamkin, Tamkin, Alex, Margalit Glasgow +5 · 1 citation
    Computer Science · Neuroscience · #Audio and Speech Processing (eess.AS) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Hearing Loss and Rehabilitation #Machine Learning (cs.LG) #Music and Audio Processing #Sound (cs.SD) #Speech and Audio Processing #electronic engineering #information engineering
  45. Emergent Symbol-like Number Variables in Artificial Neural Networks
    2025/01/10 by Satchel Grant, Noah D. Goodman, Grant, Satchel +3 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG)
  46. CriticAL: Critic Automation with Language Models
    2024/11/10 by Michael Y. Li, Vivek Vajipey, Li, Michael Y. +5 · 2 citations
    Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Multi-Agent Systems and Negotiation #Semantic Web and Ontologies
  47. Scaling up the think-aloud method
    2025/05/29 by Daniel Wurgaft, Wurgaft, Daniel, Ben Prystawski +9 · 3 voices · 2 citations
    Computer Science · Psychology · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #Child and Animal Learning Development #Computation and Language (cs.CL) #FOS: Computer and information sciences #Intelligent Tutoring Systems and Adaptive Learning #cs.AI #cs.CL
  48. Non-literal Understanding of Number Words by Language Models
    2025/02/10 by Polina Tsvilodub, Tsvilodub, Polina, Kanishk Gandhi +9 · 2 citations
    Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Mathematics, Computing, and Information Processing #Natural Language Processing Techniques #Text Readability and Simplification
  49. Human-like Affective Cognition in Foundation Models
    2024/09/18 by Kanishk Gandhi, Gandhi, Kanishk, Zoe Lynch +12 · 1 citation
    Computer Science · Neuroscience · #Cognitive Science and Education Research #Computation and Language (cs.CL) #FOS: Computer and information sciences #Psychiatry, Mental Health, Neuroscience
  50. Inferring word meanings by assuming that speakers are informative
    2014/09/17 by Michael C. Frank, Noah D. Goodman · 11 citations
    Computer Science · Neuroscience · Psychology · #Speech and dialogue systems #Neurobiology of Language and Bilingualism #Language Development and Disorders
  51. On Rate-Distortion Theory in Capacity-Limited Cognition & Reinforcement Learning
    2022/10/30 by Dilip Arumugam, Arumugam, Dilip, Mark K. Ho +5 · 1 citation
    Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics