Machine Learning · Computer Science
Learning to superoptimize programs - Workshop Version
Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr +1
2016-12-06
Computation and Language · Computer Science
SuperCoder: Assembly Program Superoptimization with Large Language Models
Anjiang Wei, Tarun Suresh, Huanmi Tan, Yinglun Xu +3
2026-02-02
Machine Learning · Computer Science
Learning to superoptimize programs
Rudy Bunel, Alban Desmaison, M. Pawan Kumar, Philip H. S. Torr +1
2017-06-29
Machine Learning · Computer Science
Learning to Superoptimize Real-world Programs
Alex Shypula, Pengcheng Yin, Jeremy Lacomis, Claire Le Goues +2
2022-04-06
Optimization and Control · Mathematics
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics
Anirudha Majumdar, Georgina Hall, Amir Ali Ahmadi
2019-12-18
Machine Learning · Computer Science
Compositional Generalization and Decomposition in Neural Program Synthesis
Kensen Shi, Joey Hong, Manzil Zaheer, Pengcheng Yin +1
2023-10-31
Distributed, Parallel, and Cluster Computing · Computer Science
A Collaborative Filtering Approach for the Automatic Tuning of Compiler Optimisations
Stefano Cereda, Gianluca Palermo, Paolo Cremonesi, Stefano Doni
2020-05-12
Software Engineering · Computer Science
Towards Evaluating Size Reduction Techniques for Software Model Checking
Gyula Sallai, Ákos Hajdu, Tamás Tóth, Zoltán Micskei
2017-08-28
Artificial Intelligence · Computer Science
Selecting Representative Examples for Program Synthesis
Yewen Pu, Zachery Miranda, Armando Solar-Lezama, Leslie Pack Kaelbling
2018-06-08
Quantum Physics · Physics
Design and synthesis of scalable quantum programs
Tomer Goldfriend, Israel Reichental, Amir Naveh, Lior Gazit +41
2025-01-24
Logic in Computer Science · Computer Science
Completeness of Synthesis under Realizability Assumptions using Superposition
Márton Hajdu, Petra Hozzová, Laura Kovács, Eva Maria Wagner
2026-05-20
Machine Learning · Computer Science
When Ensembling Smaller Models is More Efficient than Single Large Models
Dan Kondratyuk, Mingxing Tan, Matthew Brown, Boqing Gong
2020-05-05
Artificial Intelligence · Computer Science
Adaptive Neural Compilation
Rudy Bunel, Alban Desmaison, Pushmeet Kohli, Philip H. S. Torr +1
2016-05-27
Programming Languages · Computer Science
Equality Saturation: A New Approach to Optimization
Ross Tate, Michael Stepp, Zachary Tatlock, Sorin Lerner
2015-07-01