Charles Sutton

Google (United States) — United States

Computer Science · Physical Sciences

50h-index20.7kcitations206works1.32yr avg
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Research Topics

Topic Modeling(49), Software Engineering Research(48), Natural Language Processing Techniques(46), Software Testing and Debugging Techniques(20), Bayesian Modeling and Causal Inference(16)

Publications205 total

Natural Language Outlines for Code: Literate Programming in the LLM Era
2025· 2 citedOpen Access
UQE: A Query Engine for Unstructured Databases
arXiv (Cornell University)·2024· 2 citedOpen Access
UQE: A Query Engine for Unstructured Databases
2024
Universal Self-Consistency for Large Language Model Generation
arXiv (Cornell University)·2023· 9 citedOpen Access
Training Chain-of-Thought via Latent-Variable Inference
arXiv (Cornell University)·2023· 2 citedOpen Access
ExeDec: Execution Decomposition for Compositional Generalization in Neural Program Synthesis
arXiv (Cornell University)·2023Open Access
A Probabilistic Framework for Modular Continual Learning
arXiv (Cornell University)·2023Open Access
LambdaBeam: Neural Program Search with Higher-Order Functions and Lambdas
arXiv (Cornell University)·2023Open Access
Natural Language to Code Generation in Interactive Data Science Notebooks
2023· 17 citedOpen Access
Natural Language to Code Generation in Interactive Data Science Notebooks
arXiv (Cornell University)·2022· 3 citedOpen Access
A Library for Representing Python Programs as Graphs for Machine Learning
arXiv (Cornell University)·2022· 1 citedOpen Access
Language Model Cascades
arXiv (Cornell University)·2022· 20 citedOpen Access
Repairing Systematic Outliers by Learning Clean Subspaces in VAEs
arXiv (Cornell University)·2022Open Access
Compositional Generalization and Decomposition in Neural Program Synthesis
arXiv (Cornell University)·2022· 2 citedOpen Access
PaLM: Scaling Language Modeling with Pathways
arXiv (Cornell University)·2022· 2.1k citedOpen Access
CrossBeam: Learning to Search in Bottom-Up Program Synthesis
arXiv (Cornell University)·2022· 6 citedOpen Access
Conditional Independence by Typing
ACM Transactions on Programming Languages and Systems·2021Open Access
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics
Neural Information Processing Systems·2021· 9 cited
Learning Semantic Representations to Verify Hardware Designs
Neural Information Processing Systems·2021· 10 cited
Show Your Work: Scratchpads for Intermediate Computation with Language Models
arXiv (Cornell University)·2021· 16 citedOpen Access
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Frequent Co-authors

Andrew McCallum(12), Miltiadis Allamanis(10), Mingjun Zhong(5), Nigel Goddard(5), Akash Srivastava(4), Earl T. Barr(4), Maarten Bosma(2), Jacob Austin(2), Guy Gur-Ari(2), Henryk Michalewski(2), D. Dohan(2), Aitor Lewkowycz(2), Prémkumar Dévanbu(2), Khashayar Rohanimanesh(2), Chaoyun Zhang(2), Zongzuo Wang(2), Christian Bird(2), Hao Peng(2), Blaine Nelson(2), Marco Barreno(2)