Self-edit: Fault-aware code editor for code generation K Zhang, Z Li, J Li, G Li, Z Jin ACL 2023, 2023 | 109 | 2023 |
Learning to represent programs with heterogeneous graphs K Zhang, W Wang, H Zhang, G Li, Z Jin ICPC 2022, 2020 | 70 | 2020 |
Codeagent: Enhancing code generation with tool-integrated agent systems for real-world repo-level coding challenges K Zhang, J Li, G Li, X Shi, Z Jin ACL 2024, 2024 | 55 | 2024 |
Toolcoder: Teach code generation models to use api search tools K Zhang, H Zhang, G Li, J Li, Z Li, Z Jin arXiv preprint arXiv:2305.04032, 2023 | 44 | 2023 |
CodeEditor: Learning to Edit Source Code with Pre-trained Models J Li, G Li, Z Li, Z Jin, X Hu, K Zhang, Z Fu ACM Transactions on Software Engineering and Methodology 32 (6), 1-22, 2023 | 35 | 2023 |
Interpretation-based code summarization M Geng, S Wang, D Dong, H Wang, S Cao, K Zhang, Z Jin 2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC …, 2023 | 13 | 2023 |
What does transformer learn about source code? K Zhang, G Li, Z Jin arXiv preprint arXiv:2207.08466, 2022 | 11 | 2022 |
Implant global and local hierarchy information to sequence based code representation models K Zhang, Z Li, Z Jin, G Li 2023 IEEE/ACM 31st International Conference on Program Comprehension (ICPC …, 2023 | 9 | 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 | 8 | 2023 |
A tree-structured transformer for program representation learning W Wang, K Zhang, G Li, S Liu, Z Jin, Y Liu arXiv preprint arXiv:2208.08643, 2022 | 8 | 2022 |
Learning to Represent Programs with Heterogeneous Graphs.(2020) W Wang, K Zhang, G Li, Z Jin arXiv preprint cs.SE/2012.04188, 2020 | 5 | 2020 |
aiXcoder-7B: A Lightweight and Effective Large Language Model for Code Completion S Jiang, J Li, H Zong, H Liu, H Zhu, S Hu, E Li, J Ding, Y Han, W Ning, ... arXiv preprint arXiv:2410.13187, 2024 | 4 | 2024 |
Codedpo: Aligning code models with self generated and verified source code K Zhang, G Li, Y Dong, J Xu, J Zhang, J Su, Y Liu, Z Jin arXiv preprint arXiv:2410.05605, 2024 | 4 | 2024 |
Deep learning for code generation: a survey H Zhang, K Zhang, Z Li, J Li, J Li, Y Li, Y Zhao, Y Zhu, F Liu, G Li, Z Jin Science China Information Sciences 67 (9), 191101, 2024 | 4 | 2024 |
FAN: Fourier Analysis Networks Y Dong, G Li, Y Tao, X Jiang, K Zhang, J Li, J Su, J Zhang, J Xu arXiv preprint arXiv:2410.02675, 2024 | 3 | 2024 |
HiRoPE: Length Extrapolation for Code Models Using Hierarchical Position K Zhang, G Li, H Zhang, Z Jin arXiv preprint arXiv:2403.19115, 2024 | 3 | 2024 |
Revisit Self-Debugging with Self-Generated Tests for Code Generation X Chen, Z Tao, K Zhang, C Zhou, W Gu, Y He, M Zhang, X Cai, H Zhao, ... arXiv preprint arXiv:2501.12793, 2025 | 1 | 2025 |
Transformer-based code model with compressed hierarchy representation K Zhang, J Li, Z Li, Z Jin, G Li Empirical Software Engineering 30 (2), 1-43, 2025 | | 2025 |
Focused-DPO: Enhancing Code Generation Through Focused Preference Optimization on Error-Prone Points K Zhang, G Li, J Li, Y Dong, Z Jin arXiv preprint arXiv:2502.11475, 2025 | | 2025 |