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 | 160 | 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 | 82 | 2020 |
Modeling programs hierarchically with stack-augmented LSTM F Liu, L Zhang, Z Jin Journal of Systems and Software 164, 110547, 2020 | 25 | 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 | 20 | 2022 |
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 | 14 | 2022 |
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 | 13 | 2023 |
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 | 8 | 2023 |
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 |
基于深度学习的程序生成与补全技术研究进展 胡星, 李戈, 刘芳, 金芝 软件学报 30 (5), 1206-1223, 2019 | 4 | 2019 |
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 | 3 | 2024 |
程序理解: 现状与未来 金芝, 刘芳, 李戈 软件学报 30 (1), 110-126, 2018 | 3 | 2018 |
Exploring and Evaluating Hallucinations in LLM-Powered Code Generation F Liu, Y Liu, L Shi, H Huang, R Wang, Z Yang, L Zhang arXiv preprint arXiv:2404.00971, 2024 | 1 | 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 | 1 | 2023 |
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 |
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 arXiv preprint arXiv:2404.14646, 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 |
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 | | 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 | | 2024 |
MCodeSearcher: Multi-View Contrastive Learning for Code Search J Li, F Liu, J Li, Y Zhao, G Li, Z Jin Proceedings of the 14th Asia-Pacific Symposium on Internetware, 270-280, 2023 | | 2023 |
A Survey on Natural Language Processing for Programming Q Zhu, X Luo, F Liu, C Gao, W Che arXiv preprint arXiv:2212.05773, 2022 | | 2022 |