Noah Goodman
Professor of Psychology and of Computer Science
Studies the computational basis of human and machine intelligence, including probabilistic programming and language model reasoning.
Noah Goodman's lab at Stanford works on large language models, reasoning & agents and probabilistic & causal inference. 60 papers since 2023, 24 at top venues, mostly NeurIPS and ICLR. 7 PhD students. 24 alumni, most often to Apple. Applications close .
At a glance
- papers, 2023–2026
- 16/ year
- at T1 venues
- 40%
- PhD students
- 7
- MS students
- 0
- alumni listed
- 24
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 18 papers2025 · T1 6
- 21 papers2024 · T1 9
- 21 papers2023 · T1 9
T1 venuesOtherVenues: NeurIPS, ICLR, ICML, EMNLP, TMLR
Research focuspaper titles that use each topic's words
- Large language models25 papers
- Reasoning & agents12 papers
- Probabilistic & causal inference8 papers
- model reasoning1 paper
- basis0 papers
Paper list
From the lab homepage.
202518 papers
- AI for Math Workshop@ ICMLA survey on large language model reasoning failures
- PACMPL (T1)Automated Discovery of Tactic Libraries for Interactive Theorem Proving
- COLMBayesian scaling laws for in-context learning
- SEABoxingGym: Benchmarking Progress in Automated Experimental Design and Model Discovery
- JMLR (T1)Causal abstraction: A theoretical foundation for mechanistic interpretability
- Second Conference on Language Modeling (COLM), OralCognitive behaviors that enable self-improving reasoners, or, four habits of highly effective stars
- Annual Review of PsychologyCognitive modeling using artificial intelligence
- COLMD3: A dataset for training code lms to act diff-by-diff
- TMLR (T1)Emergent Symbol-like Number Variables in Artificial Neural Networks
- NeurIPS (T1)In-Context Learning Strategies Emerge Rationally
- CogSciNon-literal understanding of number words by language models
- Astrophysics Source Code LibraryNumPyro: Probabilistic programming with NumPy
202421 papers
- ICML (T1)Automated Statistical Model Discovery with Language Models
- EACLBacktracing: Retrieving the Cause of the Query
- Open MindBayesian reinforcement learning with limited cognitive load
- TMLR (T1)Certified Deductive Reasoning with Language Models
- ICML (T1)Codebook features: Sparse and discrete interpretability for neural networks
- International Educational Data Mining SocietyEvaluating and Optimizing Educational Content with Large Language Model Judgments
- CLEARFinding Alignments Between Interpretable Causal Variables and Distributed Neural Representations
- ICLR (T1)Hypothesis Search: Inductive Reasoning with Language Models
- PNAS (T1)Interaction structure constrains the emergence of conventions in group communication
- EMNLP (T1)Is Child-Directed Speech Effective Training Data for Language Models?
- Advances in Neural Information Processing Systems (NeurIPS), OralLearning Formal Mathematics From Intrinsic Motivation
- NeurIPS WorkshopMathCAMPS: Fine-grained Synthesis of Mathematical Problems From Human Curricula
202321 papers
- ICBINBCan Visual Scratchpads With Diagrammatic Abstractions Augment LLM Reasoning?
- CogSciCharacterizing tradeoffs between teaching via language and demonstrations in multi-agent systems
- CogSciCultural reinforcement learning: a framework for modeling cumulative culture on a limited channel
- NeurIPS (T1)Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
- Nature Human BehaviorFlexible social inference facilitates targeted social learning when rewards are not observable
- ICML (T1)Generating Language Corrections for Teaching Physical Control Tasks
- NeurIPS (T1)Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
- NeurIPS (T1)Learning to compress prompts with gist tokens
- CVPR-PBVSMultispectral Self-Supervised Learning with Viewmaker Networks
- Proceedings of the Annual Conference of the Cognitive Science SocietyOverinformative Question Answering by Humans and Machines
- NeurIPS (T1)Parsel: A (de-) compositional framework for algorithmic reasoning with language models
- Phil. Trans. of the Royal Society APeano: Learning Formal Mathematical Reasoning
Where alumni went24 listed, 11% to industry
Industry 1Academia 8
Most often to
- Apple
Also to
- Stanford University
- UC San Diego
- University of Michigan
Apply to StanfordFall 2027
Stanford Computer Science PhD
- Round
- Single round
- Opens
- GRE
- See program page
- English
- TOEFL/IELTS
- Fee
- See program page
Confirmed on the program page.
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