| Detecting code clones with graph neural network and flow-augmented abstract syntax tree W Wang, G Li, B Ma, X Xia, Z Jin 2020 IEEE 27th International Conference on Software Analysis, Evolution and …, 2020 | 328 | 2020 |
| The scope of chatgpt in software engineering: A thorough investigation W Ma, S Liu, W Wang, Q Hu, Y Liu, C Zhang, L Nie, Y Liu arXiv preprint arXiv:2305.12138, 2023 | 88 | 2023 |
| Learning to represent programs with heterogeneous graphs K Zhang*, W Wang*, H Zhang, G Li, Z Jin Proceedings of the 30th IEEE/ACM international conference on program …, 2022 | 69 | 2022 |
| Integrating tree path in transformer for code representation H Peng, G Li, W Wang, Y Zhao, Z Jin Advances in Neural Information Processing Systems 34, 9343-9354, 2021 | 54 | 2021 |
| Modular tree network for source code representation learning W Wang, G Li, S Shen, X Xia, Z Jin ACM Transactions on Software Engineering and Methodology (TOSEM) 29 (4), 1-23, 2020 | 54 | 2020 |
| Badedit: Backdooring large language models by model editing Y Li, T Li, K Chen, J Zhang, S Liu, W Wang, T Zhang, Y Liu arXiv preprint arXiv:2403.13355, 2024 | 53 | 2024 |
| Towards full-line code completion with neural language models W Wang, S Shen, G Li, Z Jin arXiv preprint arXiv:2009.08603, 2020 | 22 | 2020 |
| Learning program representations with a tree-structured transformer W Wang, K Zhang, G Li, S Liu, A Li, Z Jin, Y Liu 2023 IEEE International Conference on Software Analysis, Evolution and …, 2023 | 16* | 2023 |
| Unveiling code pre-trained models: Investigating syntax and semantics capacities W Ma, S Liu, M Zhao, X Xie, W Wang, Q Hu, J Zhang, Y Liu ACM Transactions on Software Engineering and Methodology 33 (7), 1-29, 2024 | 15 | 2024 |
| Lms: Understanding code syntax and semantics for code analysis W Ma, S Liu, Z Lin, W Wang, Q Hu, Y Liu, C Zhang, L Nie, L Li, Y Liu arXiv preprint arXiv:2305.12138, 2023 | 13 | 2023 |
| Are code pre-trained models powerful to learn code syntax and semantics? W Ma, M Zhao, X Xie, Q Hu, S Liu, J Zhang, W Wang, Y Liu arXiv e-prints, arXiv: 2212.10017, 2022 | 13* | 2022 |
| Testeval: Benchmarking large language models for test case generation W Wang, C Yang, Z Wang, Y Huang, Z Chu, D Song, L Zhang, AR Chen, ... arXiv preprint arXiv:2406.04531, 2024 | 11 | 2024 |
| An empirical study on noisy label learning for program understanding W Wang, Y Li, A Li, J Zhang, W Ma, Y Liu Proceedings of the IEEE/ACM 46th International Conference on Software …, 2024 | 4 | 2024 |
| Python Symbolic Execution with LLM-powered Code Generation W Wang, K Liu, AR Chen, G Li, Z Jin, G Huang, L Ma arXiv preprint arXiv:2409.09271, 2024 | 2 | 2024 |
| VulAdvisor: Natural Language Suggestion Generation for Software Vulnerability Repair J Zhang, C Wang, A Li, W Wang, T Li, Y Liu Proceedings of the 39th IEEE/ACM International Conference on Automated …, 2024 | 1 | 2024 |
| Fine-grained Testing for Autonomous Driving Software: a Study on Autoware with LLM-driven Unit Testing W Wang, X Xie, Y Huang, R Wang, AR Chen, L Ma arXiv preprint arXiv:2501.09866, 2025 | | 2025 |
| Federated Graph Learning with Adaptive Importance-based Sampling A Li, Y Chen, C Ren, W Wang, M Hu, T Li, H Yu, Q Chen arXiv preprint arXiv:2409.14655, 2024 | | 2024 |
Ge LiFull Professor of Computer Science, Peking UniversityPreverjeni e-poštni naslov na pku.edu.cn