| Codenet: A large-scale ai for code dataset for learning a diversity of coding tasks R Puri, DS Kung, G Janssen, W Zhang, G Domeniconi, V Zolotov, J Dolby, ... arXiv preprint arXiv:2105.12655, 2021 | 304 | 2021 |
| D2a: A dataset built for ai-based vulnerability detection methods using differential analysis Y Zheng, S Pujar, B Lewis, L Buratti, E Epstein, B Yang, J Laredo, ... 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | 168 | 2021 |
| Exploring Software Naturalness through Neural Language Models L Buratti, S Pujar, M Bornea, S McCarley, Y Zheng, G Rossiello, A Morari, ... arXiv preprint arXiv:2006.12641, 2020 | 117 | 2020 |
| Towards Learning (Dis)-Similarity of Source Code from Program Contrasts Y Ding, L Buratti, S Pujar, A Morari, B Ray, S Chakraborty Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 58* | 2022 |
| Beyond accuracy: Evaluating self-consistency of code llms MJ Min, Y Ding, L Buratti, S Pujar, G Kaiser, S Jana, B Ray The Twelfth International Conference on Learning Representations, 2023 | 25* | 2023 |
| Automated code generation for information technology tasks in yaml through large language models S Pujar, L Buratti, X Guo, N Dupuis, B Lewis, S Suneja, A Sood, ... 2023 60th ACM/IEEE Design Automation Conference (DAC), 1-4, 2023 | 16 | 2023 |
| Concord: clone-aware contrastive learning for source code Y Ding, S Chakraborty, L Buratti, S Pujar, A Morari, G Kaiser, B Ray Proceedings of the 32nd ACM SIGSOFT International Symposium on Software …, 2023 | 8 | 2023 |
| On Adam trained models and a parallel method to improve the generalization performance G Cong, L Buratti 2018 IEEE/ACM Machine Learning in HPC Environments (MLHPC), 85-94, 2018 | 7 | 2018 |
| Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT S Pujar, Y Zheng, L Buratti, B Lewis, Y Chen, J Laredo, A Morari, ... Empirical Software Engineering 29 (2), 48, 2024 | 6 | 2024 |
| Learning transfers over several programming languages R Baltaji, S Pujar, L Mandel, M Hirzel, L Buratti, L Varshney arXiv preprint arXiv:2310.16937, 2023 | 6 | 2023 |
| Building pre-trained contextual embeddings for programming languages using specialized vocabulary S Pujar, L Buratti, A Morari, JA Laredo, AM Gliozzo, G Rossiello US Patent 11,429,352, 2022 | 6 | 2022 |
| Vulnerability analysis using contextual embeddings S Pujar, L Buratti, A Morari, JA Laredo, AM Gliozzo, G Rossiello US Patent App. 16/917,962, 2022 | 6 | 2022 |
| Qiskit Code Assistant: Training LLMs for generating Quantum Computing Code N Dupuis, L Buratti, S Vishwakarma, AV Forrat, D Kremer, I Faro, R Puri, ... 2024 IEEE LLM Aided Design Workshop (LAD), 1-4, 2024 | 4 | 2024 |
| Ansible Lightspeed: A Code Generation Service for IT Automation P Sahoo, S Pujar, G Nalawade, R Genhardt, L Mandel, L Buratti Proceedings of the 39th IEEE/ACM International Conference on Automated …, 2024 | 2 | 2024 |
| Varangian: a git bot for augmented static analysis S Pujar, Y Zheng, L Buratti, B Lewis, A Morari, J Laredo, K Postlethwait, ... Proceedings of the 19th International Conference on Mining Software …, 2022 | 2 | 2022 |
| Qiskit HumanEval: An Evaluation Benchmark For Quantum Code Generative Models S Vishwakarma, F Harkins, S Golecha, VS Bajpe, N Dupuis, L Buratti, ... 2024 IEEE International Conference on Quantum Computing and Engineering (QCE …, 2024 | 1 | 2024 |
| Contextual embeddings for improving static analyzer output S Pujar, L Buratti, A Morari, JA Laredo, MA Bornea, JS McCarley, Y Zheng US Patent 11,765,193, 2023 | 1 | 2023 |
| Insights from the Usage of the Ansible Lightspeed Code Completion Service P Sahoo, S Pujar, G Nalawade, R Gebhardt, L Mandel, L Buratti arXiv preprint arXiv:2402.17442, 2024 | | 2024 |
| 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)| 978-1-6654-3869-8/20/$31.00© 2021 IEEE| DOI: 10.1109/ICSE … N Abburu, J Ahlgren, H Ahn, Y Ahn, D Åkerman, A Akimov, EA AlOmar, ... | | |