| Repair is nearly generation: Multilingual program repair with llms H Joshi, JC Sanchez, S Gulwani, V Le, G Verbruggen, I Radiček Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 5131-5140, 2023 | 147 | 2023 |
| Semi-supervised anomaly detection with an application to water analytics V Vercruyssen, W Meert, G Verbruggen, K Maes, R Baumer, J Davis 2018 ieee international conference on data mining (icdm) 2018, 527-536, 2018 | 113 | 2018 |
| PyDex: Repairing Bugs in Introductory Python Assignments using LLMs J Zhang, JP Cambronero, S Gulwani, V Le, R Piskac, G Soares, ... Proceedings of the ACM on Programming Languages 8 (OOPSLA), 1100-1124, 2024 | 92* | 2024 |
| Semantic programming by example with pre-trained models G Verbruggen, V Le, S Gulwani Proceedings of the ACM on Programming Languages 5 (OOPSLA), 1-25, 2021 | 35 | 2021 |
| CodeFusion: A Pre-trained Diffusion Model for Code Generation M Singh, J Cambronero, S Gulwani, V Le, C Negreanu, G Verbruggen Conference on Empirical Methods in Natural Language Processing, 11697–11708, 2023 | 27 | 2023 |
| Elements of an automatic data scientist L De Raedt, H Blockeel, S Kolb, S Teso, G Verbruggen Advances in Intelligent Data Analysis XVII: 17th International Symposium …, 2018 | 14 | 2018 |
| Cornet: Learning Table Formatting Rules By Example M Singh, JC Sánchez, S Gulwani, V Le, C Negreanu, M Raza, ... Proceedings of the VLDB Endowment 16 (10), 2632-2644, 2023 | 13* | 2023 |
| Flame: A small language model for spreadsheet formulas H Joshi, A Ebenezer, JC Sanchez, S Gulwani, A Kanade, V Le, I Radiček, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (12), 12995 …, 2024 | 10 | 2024 |
| Assessing GPT4-V on Structured Reasoning Tasks M Singh, J Cambronero, S Gulwani, V Le, G Verbruggen arXiv preprint arXiv:2312.11524, 2023 | 10 | 2023 |
| Automatically wrangling spreadsheets into machine learning data formats G Verbruggen, L De Raedt Advances in Intelligent Data Analysis XVII: 17th International Symposium …, 2018 | 9 | 2018 |
| Towards automated relational data wrangling G Verbruggen, L De Raedt Proceedings of AutoML 2017@ ECML-PKDD: Automatic selection, configuration …, 2017 | 9 | 2017 |
| Human–Machine Collaboration for Democratizing Data Science C Gautrais, Y Dauxais, S Teso, S Kolb, G Verbruggen, L De Raedt Human-Like Machine Intelligence, 379, 2021 | 8 | 2021 |
| Format5: Abstention and examples for conditional table formatting with natural language M Singh, J Cambronero, S Gulwani, V Le, C Negreanu, E Nouri, M Raza, ... Proceedings of the VLDB Endowment 17 (3), 497-510, 2023 | 6 | 2023 |
| DataVinci: Learning Syntactic and Semantic String Repairs M Singh, J Cambronero, S Gulwani, V Le, C Negreanu, A Radhakrishna, ... Proceedings of the ACM on Management of Data 3 (1), 1-26, 2025 | 3 | 2025 |
| Semantically Aligned Question and Code Generation for Automated Insight Generation A Singha, B Chopra, A Khatry, S Gulwani, A Henley, V Le, C Parnin, ... Proceedings of the 1st International Workshop on Large Language Models for …, 2024 | 3 | 2024 |
| EmFore: Online Learning of Email Folder Classification Rules M Singh, J Cambronero, S Gulwani, V Le, G Verbruggen Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 3 | 2023 |
| Program improvement using large language models J Zhang, JPC SÁNCHEZ, GA SOARES, VM Le, S Gulwani, ... US Patent App. 18/159,712, 2024 | 2 | 2024 |
| One-to-many testing for code generation from (just) natural language M Uniyal, M Singh, G Verbruggen, S Gulwani, V Le Findings of the Association for Computational Linguistics: EMNLP 2024, 15397 …, 2024 | 1 | 2024 |
| TSTR: Target Similarity Tuning Meets the Real World A Khatry, S Gulwani, P Gupta, V Le, M Singh, A Singha, G Verbruggen Findings of the Association for Computational Linguistics: EMNLP 2023, 10256 …, 2023 | 1 | 2023 |
| Sandslide: Automatic slideshow normalization S Bocklandt, G Verbruggen, T Winters International Conference on Document Analysis and Recognition, 445-461, 2021 | 1 | 2021 |
