| Pathminer: a library for mining of path-based representations of code V Kovalenko, E Bogomolov, T Bryksin, A Bacchelli 2019 IEEE/ACM 16th International Conference on Mining Software Repositories …, 2019 | 58 | 2019 |
| Out of the bleu: how should we assess quality of the code generation models? M Evtikhiev, E Bogomolov, Y Sokolov, T Bryksin Journal of Systems and Software 203, 111741, 2023 | 43 | 2023 |
| Authorship attribution of source code: A language-agnostic approach and applicability in software engineering E Bogomolov, V Kovalenko, Y Rebryk, A Bacchelli, T Bryksin Proceedings of the 29th ACM Joint Meeting on European Software Engineering …, 2021 | 39 | 2021 |
| Psiminer: A tool for mining rich abstract syntax trees from code E Spirin, E Bogomolov, V Kovalenko, T Bryksin 2021 IEEE/ACM 18th International Conference on Mining Software Repositories …, 2021 | 13 | 2021 |
| Building implicit vector representations of individual coding style V Kovalenko, E Bogomolov, T Bryksin, A Bacchelli Proceedings of the IEEE/ACM 42nd International Conference on Software …, 2020 | 8 | 2020 |
| From commit message generation to history-aware commit message completion A Eliseeva, Y Sokolov, E Bogomolov, Y Golubev, D Dig, T Bryksin 2023 38th IEEE/ACM International Conference on Automated Software …, 2023 | 7 | 2023 |
| Sosed: a tool for finding similar software projects E Bogomolov, Y Golubev, A Lobanov, V Kovalenko, T Bryksin Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 6 | 2020 |
| Evaluating the impact of source code parsers on ML4SE models I Utkin, E Spirin, E Bogomolov, T Bryksin arXiv preprint arXiv:2206.08713, 2022 | 3 | 2022 |
| Together We Go Further: LLMs and IDE Static Analysis for Extract Method Refactoring D Pomian, A Bellur, M Dilhara, Z Kurbatova, E Bogomolov, T Bryksin, ... arXiv preprint arXiv:2401.15298, 2024 | 2 | 2024 |
| Predicting tags for programming tasks by combining textual and source code data A Lobanov, E Bogomolov, Y Golubev, M Mirzayanov, T Bryksin arXiv preprint arXiv:2301.04597, 2023 | 2 | 2023 |
| Evaluation of Contrastive Learning with Various Code Representations for Code Clone Detection M Zubkov, E Spirin, E Bogomolov, T Bryksin arXiv preprint arXiv:2206.08726, 2022 | 2 | 2022 |
| Assessing project-level fine-tuning of ML4SE models E Bogomolov, S Zhuravlev, E Spirin, T Bryksin arXiv preprint arXiv:2206.03333, 2022 | 2 | 2022 |
| Unsupervised learning of general-purpose embeddings for code changes M Pravilov, E Bogomolov, Y Golubev, T Bryksin Proceedings of the 5th International Workshop on Machine Learning Techniques …, 2021 | 2 | 2021 |
| So Much in So Little: Creating Lightweight Embeddings of Python Libraries Y Golubev, E Bogomolov, E Bulychev, T Bryksin arXiv preprint arXiv:2209.03507, 2022 | 1 | 2022 |
| Tool-Augmented LLMs as a Universal Interface for IDEs Y Zharov, Y Khudyakov, E Fedotova, E Grigorenko, E Bogomolov arXiv preprint arXiv:2402.11635, 2024 | | 2024 |
Timofey BryksinJetBrains ResearchVerified email at jetbrains.com
