| Multi-task learning based pre-trained language model for code completion F Liu, G Li, Y Zhao, Z Jin Proceedings of the 35th IEEE/ACM International Conference on Automated …, 2020 | 178 | 2020 |
| A self-attentional neural architecture for code completion with multi-task learning F Liu, G Li, B Wei, X Xia, Z Fu, Z Jin Proceedings of the 28th International Conference on Program Comprehension, 37-47, 2020 | 84 | 2020 |
| Modeling programs hierarchically with stack-augmented LSTM F Liu, L Zhang, Z Jin Journal of Systems and Software 164, 110547, 2020 | 27 | 2020 |
| Learning to recommend method names with global context F Liu, G Li, Z Fu, S Lu, Y Hao, Z Jin Proceedings of the 44th International Conference on Software Engineering …, 2022 | 19 | 2022 |
| Program generation and code completion techniques based on deep learning: Literature review 胡星， 李戈， 刘芳， 金芝 Journal of Software 30 (5), 1206-1223, 2019 | 18* | 2019 |
| A unified multi-task learning model for AST-level and token-level code completion F Liu, G Li, B Wei, X Xia, Z Fu, Z Jin Empirical Software Engineering 27 (4), 91, 2022 | 17 | 2022 |
| Exploring and Evaluating Hallucinations in LLM-Powered Code Generation F Liu, Y Liu, L Shi, H Huang, R Wang, Z Yang, L Zhang, Z Li, Y Ma arXiv preprint arXiv:2404.00971v2, 2024 | 15 | 2024 |
| Large language model-aware in-context learning for code generation J Li, G Li, C Tao, H Zhang, F Liu, Z Jin arXiv preprint arXiv:2310.09748, 2023 | 14 | 2023 |
| Syntax and Domain Aware Model for Unsupervised Program Translation F Liu, J Li, L Zhang Proceedings of the 45th International Conference on Software Engineering …, 2023 | 14 | 2023 |
| Delving into Parameter-Efficient Fine-Tuning in Code Change Learning: An Empirical Study S Liu, J Keung, Z Yang, F Liu, Q Zhou, Y Liao arXiv preprint arXiv:2402.06247, 2024 | 7 | 2024 |
| 基于深度学习的程序理解研究进展 刘芳， 李戈， 胡星， 金芝 计算机研究与发展 56 (8), 1605-1620, 2019 | 6 | 2019 |
| Exploring and unleashing the power of large language models in automated code translation Z Yang, F Liu, Z Yu, JW Keung, J Li, S Liu, Y Hong, X Ma, Z Jin, G Li Proceedings of the ACM on Software Engineering 1 (FSE), 1585-1608, 2024 | 3 | 2024 |
| Non-Autoregressive Line-Level Code Completion F Liu, Z Fu, G Li, Z Jin, H Liu, Y Hao, L Zhang ACM Transactions on Software Engineering and Methodology, 2024 | 2 | 2024 |
| ZC3: Zero-Shot Cross-Language Code Clone Detection J Li, C Tao, Z Jin, F Liu, G Li 2023 38th IEEE/ACM International Conference on Automated Software …, 2023 | 2 | 2023 |
| Program Comprehension: Present and Future 金芝， 刘芳， 李戈 Journal of Software 30 (1), 110-126, 2018 | 2* | 2018 |
| A Survey on Natural Language Processing for Programming Q Zhu, X Luo, F Liu, C Gao, W Che Proceedings of the 2024 Joint International Conference on Computational …, 2024 | 1 | 2024 |
| Peer-aided Repairer: Empowering Large Language Models to Repair Advanced Student Assignments Q Zhao, F Liu, L Zhang, Y Liu, Z Yan, Z Chen, Y Zhou, J Jiang, G Li arXiv preprint arXiv:2404.01754, 2024 | 1 | 2024 |
| AdaComplete: improve DL-based code completion method’s domain adaptability Z Wang, F Liu, Y Hao, Z Jin Automated Software Engineering 30 (1), 11, 2023 | 1 | 2023 |
| Uncovering Weaknesses in Neural Code Generation X Lian, S Wang, J Ma, F Liu, X Tan, L Shi, L Zhang arXiv preprint arXiv:2407.09793, 2024 | | 2024 |
| Challenges of Using Pre-trained Models: the Practitioners' Perspective X Tan, T Li, R Chen, F Liu, L Zhang arXiv preprint arXiv:2404.14710, 2024 | | 2024 |
