| Assessing generalizability of codebert X Zhou, DG Han, D Lo 2021 IEEE International Conference on Software Maintenance and Evolution …, 2021 | 98 | 2021 |
| Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models M Weyssow, X Zhou, K Kim, D Lo, H Sahraoui arXiv preprint arXiv:2308.10462, 2023 | 62 | 2023 |
| Large language model for vulnerability detection: Emerging results and future directions X Zhou, T Zhang, D Lo Proceedings of the 2024 ACM/IEEE 44th International Conference on Software …, 2024 | 55 | 2024 |
| Out of Sight, Out of Mind: Better Automatic Vulnerability Repair by Broadening Input Ranges and Sources X Zhou, K Kim, B Xu, DG Han, D Lo Proceedings of the IEEE/ACM 46th International Conference on Software …, 2024 | 25 | 2024 |
| Representation Learning for Stack Overflow Posts: How Far are We? J He, X Zhou, B Xu, T Zhang, K Kim, Z Yang, F Thung, I Irsan, D Lo ACM Transactions on Software Engineering and Methodology, 2023 | 24 | 2023 |
| Generation-based Code Review Automation: How Far Are We? X Zhou, K Kim, B Xu, DG Han, J He, D Lo 31st IEEE/ACM International Conference on Program Comprehension (ICPC 2023), 2023 | 22 | 2023 |
| The Devil is in the Tails: How Long-Tailed Code Distributions Impact Large Language Models X Zhou, K Kim, B Xu, J Liu, DG Han, D Lo 38th IEEE/ACM International Conference on Automated Software Engineering …, 2023 | 20 | 2023 |
| Leveraging large language model for automatic patch correctness assessment X Zhou, B Xu, K Kim, DG Han, HH Nguyen, T Le-Cong, J He, B Le, D Lo IEEE Transactions on Software Engineering, 2024 | 17* | 2024 |
| CCBERT: Self-Supervised Code Change Representation Learning X Zhou, B Xu, DG Han, Z Yang, J He, D Lo 39th The International Conference on Software Maintenance and Evolution …, 2023 | 16 | 2023 |
| DexBERT: Effective, Task-Agnostic and Fine-grained Representation Learning of Android Bytecode T Sun, K Allix, K Kim, X Zhou, D Kim, D Lo, TF Bissyandé, J Klein IEEE Transactions on Software Engineering, 2023 | 16 | 2023 |
| On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-trained Language Models of Code M Weyssow, X Zhou, K Kim, D Lo, H Sahraoui The ACM Joint European Software Engineering Conference and Symposium on the …, 2023 | 15 | 2023 |
| Large Language Model for Vulnerability Detection and Repair: Literature Review and Roadmap X Zhou, S Cao, X Sun, D Lo arXiv preprint arXiv:2404.02525, 2024 | 14 | 2024 |
| Answer Summarization for Technical Queries: Benchmark and New Approach C Yang, B Xu, F Thung, Y Shi, T Zhang, Z Yang, X Zhou, J Shi, J He, ... 37th IEEE/ACM International Conference on Automated Software Engineering, 1-13, 2022 | 13 | 2022 |
| Big Code Search: a Bibliography K Kim, S Ghatpande, D Kim, X Zhou, K Liu, TF Bissyandé, J Klein, ... ACM Computing Surveys, 2022 | 11 | 2022 |
| Comparison of Static Application Security Testing Tools and Large Language Models for Repo-level Vulnerability Detection X Zhou, DM Tran, T Le-Cong, T Zhang, IC Irsan, J Sumarlin, B Le, D Lo arXiv preprint arXiv:2407.16235, 2024 | 7 | 2024 |
| Simple or complex? together for a more accurate just-in-time defect predictor X Zhou, DG Han, D Lo Proceedings of the 30th IEEE/ACM International Conference on Program …, 2022 | 7 | 2022 |
| Prioritizing speech test cases Z Yang, J Shi, MH Asyrofi, B Xu, X Zhou, DG Han, D Lo arXiv preprint arXiv:2302.00330, 2023 | 6 | 2023 |
| Bridging Expert Knowledge with Deep Learning Techniques for Just-In-Time Defect Prediction X Zhou, DG Han, D Lo arXiv preprint arXiv:2403.11079, 2024 | 2 | 2024 |
| How are We Detecting Inconsistent Method Names? An Empirical Study from Code Review Perspective K Kim, X Zhou, D Kim, J Lawall, K Liu, TF Bissyandé, J Klein, J Lee, D Lo arXiv preprint arXiv:2308.12701, 2023 | 2 | 2023 |
