| Unified Pre-training for Program Understanding and Generation WU Ahmad, S Chakraborty, B Ray, KW Chang Annual Conference of the North American Chapter of the Association for …, 2021 | 1101 | 2021 |
| Deep learning based vulnerability detection: Are we there yet? S Chakraborty, R Krishna, Y Ding, B Ray IEEE Transactions on Software Engineering 48 (9), 3280-3296, 2021 | 967 | 2021 |
| A Transformer-based Approach for Source Code Summarization W Ahmad, S Chakraborty, B Ray, KW Chang Association for Computational Linguistics, 4998--5007, 2020 | 568 | 2020 |
| Retrieval Augmented Code Generation and Summarization MR Parvez, WU Ahmad, S Chakraborty, B Ray, KW Chang Findings of the Association for Computational Linguistics 2021 (ENMLP), 2719 …, 2021 | 277 | 2021 |
| Codit: Code editing with tree-based neural models S Chakraborty, Y Ding, M Allamanis, B Ray IEEE Transactions on Software Engineering 48 (4), 1385-1399, 2020 | 232* | 2020 |
| Llm-based test-driven interactive code generation: User study and empirical evaluation S Fakhoury, A Naik, G Sakkas, S Chakraborty, SK Lahiri IEEE Transactions on Software Engineering, 2024 | 229* | 2024 |
| Natgen: generative pre-training by “naturalizing” source code S Chakraborty, T Ahmed, Y Ding, PT Devanbu, B Ray Proceedings of the 30th ACM joint european software engineering conference …, 2022 | 170 | 2022 |
| 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 | 145* | 2022 |
| Avatar: A parallel corpus for java-python program translation W Ahmad, MGR Tushar, S Chakraborty, KW Chang Findings of the Association for Computational Linguistics: ACL 2023, 2268-2281, 2023 | 133 | 2023 |
| On multi-modal learning of editing source code S Chakraborty, B Ray 2021 36th IEEE/ACM International Conference on Automated Software …, 2021 | 92 | 2021 |
| Can large language models transform natural language intent into formal method postconditions? M Endres, S Fakhoury, S Chakraborty, SK Lahiri Proceedings of the ACM on Software Engineering 1 (FSE), 1889-1912, 2024 | 81* | 2024 |
| Building language models for text with named entities MR Parvez, S Chakraborty, B Ray, KW Chang 56th Annual Meeting of the Association for Computational Linguistics 1 (Long …, 2018 | 64* | 2018 |
| Leveraging llms for program verification A Kamath, N Mohammed, A Senthilnathan, S Chakraborty, P Deligiannis, ... 2024 Formal Methods in Computer-Aided Design (FMCAD), 107-118, 2024 | 61* | 2024 |
| Ranking llm-generated loop invariants for program verification S Chakraborty, S Lahiri, S Fakhoury, A Lal, M Musuvathi, A Rastogi, ... Findings of the Association for Computational Linguistics: EMNLP 2023, 9164-9175, 2023 | 61 | 2023 |
| Towards causal deep learning for vulnerability detection MM Rahman, I Ceka, C Mao, S Chakraborty, B Ray, W Le Proceedings of the IEEE/ACM 46th international conference on software …, 2024 | 48 | 2024 |
| Studying llm performance on closed-and open-source data T Ahmed, C Bird, P Devanbu, S Chakraborty arXiv preprint arXiv:2402.15100, 2024 | 43 | 2024 |
| Summarize and Generate to Back-translate: Unsupervised Translation of Programming Languages W Uddin Ahmad, S Chakraborty, B Ray, KW Chang arXiv e-prints, arXiv: 2205.11116, 2022 | 39* | 2022 |
| A heuristic initialized stochastic memetic algorithm for MDPVRP with interdependent depot operations AS Azad, M Islam, S Chakraborty IEEE Transactions on Cybernetics 47 (12), 4302-4315, 2017 | 36 | 2017 |
| Grace: Generation using associated code edits P Gupta, A Khare, Y Bajpai, S Chakraborty, S Gulwani, A Kanade, ... arXiv preprint arXiv:2305.14129, 2023 | 33* | 2023 |
| Towards generating functionally correct code edits from natural language issue descriptions S Fakhoury, S Chakraborty, M Musuvathi, SK Lahiri arXiv preprint arXiv:2304.03816, 2023 | 30 | 2023 |
Baishakhi RayAssociate Professor, Columbia UniversityVerified email at cs.columbia.edu
