Congruence Subgroups of PSL(2, Z) of Genus Less than or Equal to 24. - Chris Cummins; Sebastian Pauli (Exp. Math., 2003)

Congruence Subgroups of Groups Commensurable with PSL (2, Z) of Genus 0 and 1. - Chris Cummins (Exp. Math., 2004)

Elliptic curves with nonsplit mod 11 representations. - Imin Chen; Chris Cummins (Math. Comput., 2004)

Comparative and Superlative Quantifiers: Pragmatic Effects of Comparison Type. - Chris Cummins; Napoleon Katsos (J. Semant., 2010)

Pragmatics: From Theory to Experiment and Back Again. - Napoleon Katsos; Chris Cummins (Lang. Linguistics Compass, 2010)

Teaching and Learning Guide for: Pragmatics: From Theory to Experiment and Back Again. - Napoleon Katsos; Chris Cummins (Lang. Linguistics Compass, 2010)

A Speaker-Referring OT Pragmatics of Quantity Expressions. - Chris Cummins (CSLP, 2012)

Priming and Conceptual Pacts in Overhearers' Adoption of Referring Expressions. - Marieke Behnel; Chris Cummins; Lorenz Sichelschmidt; Jan P. de Ruiter (CogSci, 2013)

Computational Approaches to the Pragmatics Problem. - Chris Cummins; Jan P. de Ruiter (Lang. Linguistics Compass, 2014)

Autotuning OpenCL Workgroup Size for Stencil Patterns. - Chris Cummins; Pavlos Petoumenos; Michel Steuwer; Hugh Leather (CoRR, 2015)

Teaching and Learning Guide for Computational Approaches to the Pragmatics Problem. - Chris Cummins; Jan P. de Ruiter (Lang. Linguistics Compass, 2015)

Modelling the co-development of word learning and perspective-taking. - Marieke Woensdregt; Simon Kirby; Chris Cummins; Kenny Smith (CogSci, 2016)

End-to-End Deep Learning of Optimization Heuristics. - Chris Cummins; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (PACT, 2017)

Synthesizing benchmarks for predictive modeling. - Chris Cummins; Pavlos Petoumenos; Zheng Wang 001; Hugh Leather (CGO, 2017)

A model of cultural co-evolution of language and mindreading. - Marieke Woensdregt; Simon Kirby; Chris Cummins; Kenny Smith (CogSci, 2017)

Training and Timing Local Scalar Enrichments under Global Pragmatic Pressures. - Emmanuel Chemla; Chris Cummins; Raj Singh (J. Semant., 2017)

Compiler fuzzing through deep learning. - Chris Cummins; Pavlos Petoumenos; Alastair Murray; Hugh Leather (ISSTA, 2018)

A case study on machine learning for synthesizing benchmarks. - Andrés Goens; Alexander Brauckmann; Sebastian Ertel; Chris Cummins; Hugh Leather; Jerónimo Castrillón (MAPL@PLDI, 2019)

Modeling manipulative language use. - Vinicius Macuch Silva; Chris Cummins; Michael Franke (CogSci, 2020)

Machine Learning in Compilers: Past, Present and Future. - Hugh Leather; Chris Cummins (FDL, 2020)

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis. - Chris Cummins; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Hugh Leather (CoRR, 2020)

Value Function Based Performance Optimization of Deep Learning Workloads. - Benoit Steiner; Chris Cummins; Horace He; Hugh Leather (CoRR, 2020)

Deep Data Flow Analysis. - Chris Cummins; Hugh Leather; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Michael F. P. O'Boyle (CoRR, 2020)

ProGraML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations. - Chris Cummins; Zacharias V. Fisches; Tal Ben-Nun; Torsten Hoefler; Michael F. P. O'Boyle; Hugh Leather (ICML, 2021)

Value Learning for Throughput Optimization of Deep Learning Workloads. - Benoit Steiner; Chris Cummins; Horace He; Hugh Leather (MLSys, 2021)

Learning Space Partitions for Path Planning. - Kevin Yang; Tianjun Zhang; Chris Cummins; Brandon Cui; Benoit Steiner; Linnan Wang; Joseph E. Gonzalez; Dan Klein 001; Yuandong Tian (NeurIPS, 2021)

Profile Guided Optimization without Profiles: A Machine Learning Approach. - Nadav Rotem; Chris Cummins (CoRR, 2021)

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. - Cheng Fu 002; Hanxian Huang; Bram Wasti; Chris Cummins; Riyadh Baghdadi; Kim M. Hazelwood; Yuandong Tian; Jishen Zhao; Hugh Leather (PACT, 2022)

BenchPress: A Deep Active Benchmark Generator. - Foivos Tsimpourlas; Pavlos Petoumenos; Min Xu; Chris Cummins; Kim M. Hazelwood; Ajitha Rajan; Hugh Leather (PACT, 2022)

Caviar: an e-graph based TRS for automatic code optimization. - Smail Kourta; Adel Abderahmane Namani; Fatima Benbouzid-Si Tayeb; Kim M. Hazelwood; Chris Cummins; Hugh Leather; Riyadh Baghdadi (CC, 2022)

Automating reinforcement learning architecture design for code optimization. - Huanting Wang; Zhanyong Tang; Cheng Zhang 007; Jiaqi Zhao; Chris Cummins; Hugh Leather; Zheng Wang 001 (CC, 2022)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. - Youwei Liang; Kevin Stone; Ali Shameli; Chris Cummins; Mostafa Elhoushi; Jiadong Guo; Benoit Steiner; Xiaomeng Yang; Pengtao Xie; Hugh James Leather; Yuandong Tian (ICML, 2023)

BenchDirect: A Directed Language Model for Compiler Benchmarks. - Foivos Tsimpourlas; Pavlos Petoumenos; Min Xu; Chris Cummins; Kim M. Hazelwood; Ajitha Rajan; Hugh Leather (CoRR, 2023)

SLaDe: A Portable Small Language Model Decompiler for Optimized Assembler. - Jordi Armengol-Estapé; Jackson Woodruff; Chris Cummins; Michael F. P. O'Boyle (CoRR, 2023)

LoopTune: Optimizing Tensor Computations with Reinforcement Learning. - Dejan Grubisic; Bram Wasti; Chris Cummins; John M. Mellor-Crummey; Aleksandar Zlateski (CoRR, 2023)

Large Language Models for Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Mostafa Elhoushi; Youwei Liang; Baptiste Rozière; Jonas Gehring; Fabian Gloeckle; Kim M. Hazelwood; Gabriel Synnaeve; Hugh Leather (CoRR, 2023)

Rewriting History: Repurposing Domain-Specific CGRAs. - Jackson Woodruff; Thomas Koehler; Alexander Brauckmann; Chris Cummins; Sam Ainsworth; Michael F. P. O'Boyle (CoRR, 2023)

SLaDe: A Portable Small Language Model Decompiler for Optimized Assembly. - Jordi Armengol-Estapé; Jackson Woodruff; Chris Cummins; Michael F. P. O'Boyle (CGO, 2024)

Revealing Compiler Heuristics Through Automated Discovery and Optimization. - Volker Seeker; Chris Cummins; Murray Cole; Björn Franke; Kim M. Hazelwood; Hugh Leather (CGO, 2024)

Priority Sampling of Large Language Models for Compilers. - Dejan Grubisic; Volker Seeker; Gabriel Synnaeve; Hugh Leather; John M. Mellor-Crummey; Chris Cummins (EuroMLSys@EuroSys, 2024)

Priority Sampling of Large Language Models for Compilers. - Dejan Grubisic; Chris Cummins; Volker Seeker; Hugh Leather (CoRR, 2024)

Compiler generated feedback for Large Language Models. - Dejan Grubisic; Chris Cummins; Volker Seeker; Hugh Leather (CoRR, 2024)

Meta Large Language Model Compiler: Foundation Models of Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Baptiste Rozière; Jonas Gehring; Gabriel Synnaeve; Hugh Leather (CoRR, 2024)

Don't Transform the Code, Code the Transforms: Towards Precise Code Rewriting using LLMs. - Chris Cummins; Volker Seeker; Jordi Armengol-Estapé; Aram H. Markosyan; Gabriel Synnaeve; Hugh Leather (CoRR, 2024)

LLM Compiler: Foundation Language Models for Compiler Optimization. - Chris Cummins; Volker Seeker; Dejan Grubisic; Baptiste Rozière; Jonas Gehring; Gabriel Synnaeve; Hugh Leather (CC, 2025)

Finding Missed Code Size Optimizations in Compilers using Large Language Models. - Davide Italiano; Chris Cummins (CC, 2025)

Finding Missed Code Size Optimizations in Compilers using LLMs. - Davide Italiano; Chris Cummins (CoRR, 2025)

What I cannot execute, I do not understand: Training and Evaluating LLMs on Program Execution Traces. - Jordi Armengol-Estapé; Quentin Carbonneaux; Tianjun Zhang; Aram H. Markosyan; Volker Seeker; Chris Cummins; Melanie Kambadur; Michael F. P. O'Boyle; Sida I. Wang; Gabriel Synnaeve; Hugh James Leather (CoRR, 2025)