| 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 | 96 | 2018 |
| 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 | 71 | 2023 |
| Repairing Bugs in Python Assignments Using Large Language Models J Zhang, J Cambronero, S Gulwani, V Le, R Piskac, G Soares, ... arXiv preprint arXiv:2209.14876, 2022 | 42 | 2022 |
| 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 | 24 | 2021 |
| 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 | 15 | 2018 |
| 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 |
| CodeFusion: A Pre-trained Diffusion Model for Code Generation M Singh, J Cambronero, S Gulwani, V Le, C Negreanu, G Verbruggen arXiv preprint arXiv:2310.17680, 2023 | 8 | 2023 |
| 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 | 7 | 2021 |
| CORNET: A neurosymbolic approach to learning conditional table formatting rules by example M Singh, J Cambronero, S Gulwani, V Le, C Negreanu, M Raza, ... arXiv preprint arXiv:2208.06032, 2022 | 5 | 2022 |
| 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 |
| 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, ... arXiv preprint arXiv:2310.17306, 2023 | 2 | 2023 |
| 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 | 2 | 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 | 1 | 2024 |
| Assessing GPT4-V on Structured Reasoning Tasks M Singh, J Cambronero, S Gulwani, V Le, G Verbruggen arXiv preprint arXiv:2312.11524, 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 |
| SynthLog: A Language for Synthesising Inductive Data Models Y Dauxais, C Gautrais, A Dries, A Jain, S Kolb, M Kumar, S Teso, ... Machine Learning and Knowledge Discovery in Databases: International …, 2020 | 1 | 2020 |
| EmFORE: Learning Email Folder Classification Rules by Demonstration M Singh, G Verbruggen, J Cambronero, V Le, S Gulwani Proceedings of the AAAI Conference on Artificial Intelligence 38 (21), 23835 …, 2024 | | 2024 |
| Semantically Aligned Question and Code Generation for Automated Insight Generation A Singha, B Chopra, A Khatry, S Gulwani, AZ Henley, V Le, C Parnin, ... | | 2024 |
| TSTR: Target Similarity Tuning Meets the Real World A Khatry, S Gulwani, P Gupta, V Le, M Singh, A Singha, G Verbruggen The 2023 Conference on Empirical Methods in Natural Language Processing, 2023 | | 2023 |
