| Codexglue: A machine learning benchmark dataset for code understanding and generation S Lu, D Guo, S Ren, J Huang, A Svyatkovskiy, A Blanco, C Clement, ... arXiv preprint arXiv:2102.04664, 2021 | 1073* | 2021 |
| Graphcodebert: Pre-training code representations with data flow D Guo, S Ren, S Lu, Z Feng, D Tang, S Liu, L Zhou, N Duan, ... arXiv preprint arXiv:2009.08366, 2020 | 976 | 2020 |
| PyMT5: multi-mode translation of natural language and python code with transformers C Clement, D Drain, T Jonathan, A Svyatkovskiy, N Sundaresan Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 162* | 2020 |
| Phase Diagram of Electrostatically Doped Y Lee, C Clement, J Hellerstedt, J Kinney, L Kinnischtzke, X Leng, ... Physical Review Letters 106 (13), 136809, 2011 | 152 | 2011 |
| On the use of arxiv as a dataset CB Clement, M Bierbaum, KP O'Keeffe, AA Alemi arXiv preprint arXiv:1905.00075, 2019 | 109 | 2019 |
| Image registration of low signal-to-noise cryo-STEM data BH Savitzky, I El Baggari, CB Clement, E Waite, BH Goodge, DJ Baek, ... Ultramicroscopy 191, 56-65, 2018 | 91 | 2018 |
| Training and Evaluating a Jupyter Notebook Data Science Assistant S Chandel, CB Clement, G Serrato, N Sundaresan arXiv preprint arXiv:2201.12901, 2022 | 51 | 2022 |
| Learning to reduce false positives in analytic bug detectors A Kharkar, RZ Moghaddam, M Jin, X Liu, X Shi, C Clement, ... Proceedings of the 44th International Conference on Software Engineering …, 2022 | 40 | 2022 |
| Deepdebug: Fixing python bugs using stack traces, backtranslation, and code skeletons D Drain, CB Clement, G Serrato, N Sundaresan arXiv preprint arXiv:2105.09352, 2021 | 32 | 2021 |
| Normal Form for Renormalization Groups A Raju, CB Clement, LX Hayden, JP Kent-Dobias, DB Liarte, DZ Rocklin, ... Physical Review X, 0 | 31* | |
| Execution-based evaluation for data science code generation models J Huang, C Wang, J Zhang, C Yan, H Cui, JP Inala, C Clement, N Duan, ... arXiv preprint arXiv:2211.09374, 2022 | 30 | 2022 |
| Visualizing probabilistic models and data with Intensive Principal Component Analysis KN Quinn, CB Clement, F De Bernardis, MD Niemack, JP Sethna Proceedings of the National Academy of Sciences 116 (28), 13762-13767, 2019 | 28 | 2019 |
| Long-range modeling of source code files with ewash: Extended window access by syntax hierarchy C Clement, S Lu, X Liu, M Tufano, N Duan, Nan, Sundaresan, ... Proceedings of the 2021 Conference on Empirical Methods in Natural Language …, 2021 | 23* | 2021 |
| Automatic generation of code documentation CB Clement, J Drain, N Sundaresan, A Svyatkovskiy US Patent App. 16/897,813, 2021 | 21 | 2021 |
| Neural method completion based on natural language and source code CB Clement, D Drain, N Sundaresan, A Svyatkovskiy US Patent 11,972,232, 2024 | 14 | 2024 |
| Deepdev-perf: a deep learning-based approach for improving software performance S Garg, RZ Moghaddam, CB Clement, N Sundaresan, C Wu Proceedings of the 30th ACM Joint European Software Engineering Conference …, 2022 | 14 | 2022 |
| Visualizing probabilistic models in Minkowski space with intensive symmetrized Kullback-Leibler embedding HK Teoh, KN Quinn, J Kent-Dobias, CB Clement, Q Xu, JP Sethna Physical Review Research 2 (3), 033221, 2020 | 14 | 2020 |
| Transfer learning system for automated software engineering tasks CB Clement, D Drain, N Sundaresan, A Svyatkovskiy US Patent 11,521,075, 2022 | 13 | 2022 |
| Predicting code coverage without execution M Tufano, S Chandel, A Agarwal, N Sundaresan, C Clement arXiv preprint arXiv:2307.13383, 2023 | 12 | 2023 |
| On the use of ArXiv as a dataset (2019) CB Clement, M Bierbaum, KP O’Keeffe, AA Alemi arXiv preprint arXiv:1905.00075, 1905 | 8 | 1905 |
Alexey SvyatkovskiyGoogle DeepMindVerified email at google.com