Devign: Effective vulnerability identification by learning comprehensive program semantics via graph neural networks Y Zhou, S Liu, J Siow, X Du, Y Liu Advances in Neural Information Processing Systems, 10197-10207, 2019 | 540 | 2019 |
Retrieval-augmented generation for code summarization via hybrid gnn S Liu, Y Chen, X Xie, J Siow, Y Liu International Conference on Learning Representations, 2020 | 123* | 2020 |
ATOM: Commit message generation based on abstract syntax tree and hybrid ranking S Liu, C Gao, S Chen, LY Nie, Y Liu IEEE Transactions on Software Engineering 48 (5), 1800-1817, 2020 | 70 | 2020 |
DeepCount: Crowd counting with Wi-Fi using deep learning Y Zhao, S Liu, F Xue, B Chen, X Chen Journal of Communications and Information Networks 4 (3), 38-52, 2019 | 69* | 2019 |
WiCount: A deep learning approach for crowd counting using WiFi signals S Liu, Y Zhao, B Chen 2017 IEEE International Symposium on Parallel and Distributed Processing …, 2017 | 49 | 2017 |
SPI: Automated Identification of Security Patches via Commits Y Zhou, JK Siow, C Wang, S Liu, Y Liu ACM Transactions on Software Engineering and Methodology (TOSEM) 31 (1), 1-27, 2021 | 37 | 2021 |
Learning Program Semantics with Code Representations: An Empirical Study JK Siow, S Liu, X Xie, G Meng, Y Liu 2022 IEEE International Conference on Software Analysis, Evolution and …, 2022 | 27 | 2022 |
GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search S Liu, X Xie, J Siow, L Ma, G Meng, Y Liu IEEE Transactions on Software Engineering, 2021 | 24 | 2021 |
Do different cross‐project defect prediction methods identify the same defective modules? X Chen, Y Mu, Y Qu, C Ni, M Liu, T He, S Liu Journal of Software: Evolution and Process 32 (5), e2234, 2020 | 17 | 2020 |
Enhancing security patch identification by capturing structures in commits B Wu, S Liu, R Feng, X Xie, J Siow, SW Lin IEEE Transactions on Dependable and Secure Computing, 2022 | 16 | 2022 |
Device-free secure interaction with hand gestures in WiFi-enabled IoT environment Y Zhao, R Gao, S Liu, L Xie, J Wu, H Tu, B Chen IEEE Internet of Things Journal 8 (7), 5619-5631, 2020 | 14 | 2020 |
ContraBERT: Enhancing Code Pre-trained Models via Contrastive Learning S Liu, B Wu, X Xie, G Meng, Y Liu The 45th IEEE/ACM International Conference on Software Engineering, 2023 | 13 | 2023 |
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 | 12 | 2023 |
TransRepair: Context-aware Program Repair for Compilation Errors X Li, S Liu, R Feng, G Meng, X Xie, K Chen, Y Liu Proceedings of the 37th ACM/IEEE International Conference on Automated …, 2022 | 12 | 2022 |
A unified framework to learn program semantics with graph neural networks S Liu Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 11 | 2020 |
Commitbart: A large pre-trained model for github commits S Liu, Y Li, X Xie, Y Liu arXiv preprint arXiv:2208.08100, 2022 | 8 | 2022 |
Multi-target Backdoor Attacks for Code Pre-trained Models Y Li, S Liu, K Chen, X Xie, T Zhang, Y Liu The 61st Annual Meeting of the Association for Computational Linguistics., 2023 | 6 | 2023 |
Evaluating AIGC Detectors on Code Content J Wang, S Liu, X Xie, Y Li arXiv preprint arXiv:2304.05193, 2023 | 6 | 2023 |
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 | 4* | 2023 |
Are Code Pre-trained Models Powerful to Learn Code Syntax and Semantics? W Ma, S Liu, M Zhao, Q Hu, J Zhang, W Wang, Y Liu | 2* | |