Alexey Svyatkovskiy

According to our database, Alexey Svyatkovskiy authored at least 32 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

DeepMerge: Learning to Merge Programs.

Elizabeth Dinella, Todd Mytkowicz, Alexey Svyatkovskiy, Christian Bird, Mayur Naik, Shuvendu K. Lahiri

IEEE Trans. Software Eng., April, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.

Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens

CoRR, 2023

Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation.

Benjamin Steenhoek, Michele Tufano, Neel Sundaresan, Alexey Svyatkovskiy

CoRR, 2023

AdaptivePaste: Intelligent Copy-Paste in IDE.

Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis, Alexey Svyatkovskiy

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

InferFix: End-to-End Program Repair with LLMs.

Matthew Jin, Syed Shahriar, Michele Tufano, Xin Shi, Shuai Lu, Neel Sundaresan, Alexey Svyatkovskiy

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

Code Execution with Pre-trained Language Models.

Chenxiao Liu, Shuai Lu, Weizhu Chen, Daxin Jiang, Alexey Svyatkovskiy, Shengyu Fu, Neel Sundaresan, Nan Duan

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

AdaptivePaste: Code Adaptation through Learning Semantics-aware Variable Usage Representations.

Xiaoyu Liu, Jinu Jang, Neel Sundaresan, Miltiadis Allamanis, Alexey Svyatkovskiy

CoRR, 2022

CodeReviewer: Pre-Training for Automating Code Review Activities.

Zhiyu Li, Shuai Lu, Daya Guo, Nan Duan, Shailesh Jannu, Grant Jenks, Deep Majumder, Jared Green, Alexey Svyatkovskiy, Shengyu Fu, Neel Sundaresan

CoRR, 2022

Exploring and evaluating personalized models for code generation.

Andrei Zlotchevski, Dawn Drain, Alexey Svyatkovskiy, Colin B. Clement, Neel Sundaresan, Michele Tufano

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

Program merge conflict resolution via neural transformers.

Alexey Svyatkovskiy, Sarah Fakhoury, Negar Ghorbani, Todd Mytkowicz, Elizabeth Dinella, Christian Bird, Jinu Jang, Neel Sundaresan, Shuvendu K. Lahiri

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

Automating code review activities by large-scale pre-training.

Zhiyu Li, Shuai Lu, Daya Guo, Nan Duan, Shailesh Jannu, Grant Jenks, Deep Majumder, Jared Green, Alexey Svyatkovskiy, Shengyu Fu, Neel Sundaresan

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

METHODS2TEST: A dataset of focal methods mapped to test cases.

Michele Tufano, Shao Kun Deng, Neel Sundaresan, Alexey Svyatkovskiy

Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022

Learning to Complete Code with Sketches.

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

Proceedings of the Tenth International Conference on Learning Representations, 2022

Generating Accurate Assert Statements for Unit Test Cases using Pretrained Transformers.

Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Neel Sundaresan

Proceedings of the IEEE/ACM International Conference on Automation of Software Test, 2022

ReACC: A Retrieval-Augmented Code Completion Framework.

Shuai Lu, Nan Duan, Hojae Han, Daya Guo, Seung-won Hwang, Alexey Svyatkovskiy

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

MergeBERT: Program Merge Conflict Resolution via Neural Transformers.

Alexey Svyatkovskiy, Todd Mytkowicz, Negar Ghorbani, Sarah Fakhoury, Elizabeth Dinella, Christian Bird, Neel Sundaresan, Shuvendu K. Lahiri

CoRR, 2021

Learning to Generate Code Sketches.

Daya Guo, Alexey Svyatkovskiy, Jian Yin, Nan Duan, Marc Brockschmidt, Miltiadis Allamanis

CoRR, 2021

Generating bug-fixes using pretrained transformers.

Dawn Drain, Chen Wu, Alexey Svyatkovskiy, Neel Sundaresan

Proceedings of the MAPS@PLDI 2021: Proceedings of the 5th ACM SIGPLAN International Symposium on Machine Programming, 2021

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation.

Shuai Lu, Daya Guo, Shuo Ren, Junjie Huang, Alexey Svyatkovskiy, Ambrosio Blanco, Colin B. Clement, Dawn Drain, Daxin Jiang, Duyu Tang, Ge Li, Lidong Zhou, Linjun Shou, Long Zhou, Michele Tufano, Ming Gong, Ming Zhou, Nan Duan, Neel Sundaresan, Shao Kun Deng, Shengyu Fu, Shujie Liu

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Fast and Memory-Efficient Neural Code Completion.

Alexey Svyatkovskiy, Sebastian Lee, Anna Hadjitofi, Maik Riechert, Juliana Vicente Franco, Miltiadis Allamanis

Proceedings of the 18th IEEE/ACM International Conference on Mining Software Repositories, 2021

GraphCodeBERT: Pre-training Code Representations with Data Flow.

Daya Guo, Shuo Ren, Shuai Lu, Zhangyin Feng, Duyu Tang, Shujie Liu, Long Zhou, Nan Duan, Alexey Svyatkovskiy, Shengyu Fu, Michele Tufano, Shao Kun Deng, Colin B. Clement, Dawn Drain, Neel Sundaresan, Jian Yin, Daxin Jiang, Ming Zhou

Proceedings of the 9th International Conference on Learning Representations, 2021

Long-Range Modeling of Source Code Files with eWASH: Extended Window Access by Syntax Hierarchy.

Colin B. Clement, Shuai Lu, Xiaoyu Liu, Michele Tufano, Dawn Drain, Nan Duan, Neel Sundaresan, Alexey Svyatkovskiy

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Unit Test Case Generation with Transformers.

Michele Tufano, Dawn Drain, Alexey Svyatkovskiy, Shao Kun Deng, Neel Sundaresan

CoRR, 2020

IntelliCode compose: code generation using transformer.

Alexey Svyatkovskiy, Shao Kun Deng, Shengyu Fu, Neel Sundaresan

Proceedings of the ESEC/FSE '20: 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2020

PyMT5: multi-mode translation of natural language and Python code with transformers.

Colin B. Clement, Dawn Drain, Jonathan Timcheck, Alexey Svyatkovskiy, Neel Sundaresan

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Predicting disruptive instabilities in controlled fusion plasmas through deep learning.

Julian Kates-Harbeck, Alexey Svyatkovskiy, William Tang

Nat., 2019

Using Big Data Technologies for HEP Analysis.

Matteo Cremonesi, Claudio Bellini, Bianny Bian, Luca Canali, Vasileios Dimakopoulos, Peter Elmer, Ian Fisk, Maria Girone, Oliver Gutsche, Siew-Yan Hoh, Bo Jayatilaka, Viktor Khristenko, Andrea Luiselli, Andrew Melo, Evangelos Motesnitsalis, Dominick Olivito, Jacopo Pazzini, Jim Pivarski, Alexey Svyatkovskiy, Marco Zanetti

CoRR, 2019

Pythia: AI-assisted Code Completion System.

Alexey Svyatkovskiy, Ying Zhao, Shengyu Fu, Neel Sundaresan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2017

CMS Analysis and Data Reduction with Apache Spark.

Oliver Gutsche, Luca Canali, Illia Cremer, Matteo Cremonesi, Peter Elmer, Ian Fisk, Maria Girone, Bo Jayatilaka, Jim Kowalkowski, Viktor Khristenko, Evangelos Motesnitsalis, Jim Pivarski, Saba Sehrish, Kacper Surdy, Alexey Svyatkovskiy

CoRR, 2017

Big Data in HEP: A comprehensive use case study.

Oliver Gutsche, Matteo Cremonesi, Peter Elmer, Bo Jayatilaka, Jim Kowalkowski, Jim Pivarski, Saba Sehrish, Cristina Mantilla Suarez, Alexey Svyatkovskiy, Nhan Tran

CoRR, 2017

Training distributed deep recurrent neural networks with mixed precision on GPU clusters.

Alexey Svyatkovskiy, Julian Kates-Harbeck, William Tang

Proceedings of the Machine Learning on HPC Environments, 2017

2016

Large-scale text processing pipeline with Apache Spark.

Alexey Svyatkovskiy, Kosuke Imai, Mary Kroeger, Yuki Shiraito

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016