| 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 | 1102* | 2020 |
| 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 | 996* | 2021 |
| Unixcoder: Unified cross-modal pre-training for code representation D Guo, S Lu, N Duan, Y Wang, M Zhou, J Yin arXiv preprint arXiv:2203.03850, 2022 | 481 | 2022 |
| Codebleu: a method for automatic evaluation of code synthesis S Ren, D Guo, S Lu, L Zhou, S Liu, D Tang, N Sundaresan, M Zhou, ... arXiv preprint arXiv:2009.10297, 2020 | 364 | 2020 |
| Summarizing source code with transferred api knowledge X Hu, G Li, X Xia, D Lo, S Lu, Z Jin | 319 | 2018 |
| Agieval: A human-centric benchmark for evaluating foundation models W Zhong, R Cui, Y Guo, Y Liang, S Lu, Y Wang, A Saied, W Chen, ... arXiv preprint arXiv:2304.06364, 2023 | 249 | 2023 |
| Taskmatrix. ai: Completing tasks by connecting foundation models with millions of apis Y Liang, C Wu, T Song, W Wu, Y Xia, Y Liu, Y Ou, S Lu, L Ji, S Mao, ... Intelligent Computing 3, 0063, 2024 | 146 | 2024 |
| Automating code review activities by large-scale pre-training Z Li, S Lu, D Guo, N Duan, S Jannu, G Jenks, D Majumder, J Green, ... Proceedings of the 30th ACM Joint European Software Engineering Conference …, 2022 | 142* | 2022 |
| Inferfix: End-to-end program repair with llms M Jin, S Shahriar, M Tufano, X Shi, S Lu, N Sundaresan, A Svyatkovskiy Proceedings of the 31st ACM Joint European Software Engineering Conference …, 2023 | 110 | 2023 |
| Reacc: A retrieval-augmented code completion framework S Lu, N Duan, H Han, D Guo, S Hwang, A Svyatkovskiy arXiv preprint arXiv:2203.07722, 2022 | 100 | 2022 |
| WhiteningBERT: An easy unsupervised sentence embedding approach J Huang, D Tang, W Zhong, S Lu, L Shou, M Gong, D Jiang, N Duan arXiv preprint arXiv:2104.01767, 2021 | 97 | 2021 |
| Why do neural dialog systems generate short and meaningless replies? a comparison between dialog and translation B Wei, S Lu, L Mou, H Zhou, P Poupart, G Li, Z Jin ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 37 | 2019 |
| Code execution with pre-trained language models C Liu, S Lu, W Chen, D Jiang, A Svyatkovskiy, S Fu, N Sundaresan, ... arXiv preprint arXiv:2305.05383, 2023 | 25 | 2023 |
| Learning to recommend method names with global context F Liu, G Li, Z Fu, S Lu, Y Hao, Z Jin Proceedings of the 44th International Conference on Software Engineering …, 2022 | 22 | 2022 |
| Enhancing large language models in coding through multi-perspective self-consistency B Huang, S Lu, W Chen, X Wan, N Duan arXiv preprint arXiv:2309.17272, 2023 | 11 | 2023 |
| Competition-level problems are effective llm evaluators Y Huang, Z Lin, X Liu, Y Gong, S Lu, F Lei, Y Liang, Y Shen, C Lin, ... Findings of the Association for Computational Linguistics ACL 2024, 13526-13544, 2024 | 8 | 2024 |
| Long-range modeling of source code files with eWASH: Extended window access by syntax hierarchy CB Clement, S Lu, X Liu, M Tufano, D Drain, N Duan, N Sundaresan, ... arXiv preprint arXiv:2109.08780, 2021 | 8 | 2021 |
| CodeBERT‐Attack: Adversarial attack against source code deep learning models via pre‐trained model H Zhang, S Lu, Z Li, Z Jin, L Ma, Y Liu, G Li Journal of Software: Evolution and Process 36 (3), e2571, 2024 | 6 | 2024 |
| Multi-lingual code generation with zero-shot inference CB Clement, S Lu, N Sundaresan, A Svyatkovskiy, D Tang US Patent 11,693,630, 2023 | 5 | 2023 |
| Selene: Pioneering Automated Proof in Software Verification L Zhang, S Lu, N Duan arXiv preprint arXiv:2401.07663, 2024 | 2 | 2024 |
Nan DuanSenior Principal Research Manager, Microsoft ResearchVerified email at microsoft.com
