| Dynamic network embedding: An extended approach for skip-gram based network embedding. L Du, Y Wang, G Song, Z Lu, J Wang IJCAI 2018, 2086-2092, 2018 | 243 | 2018 |
| GBK-GNN: Gated bi-kernel graph neural networks for modeling both homophily and heterophily L Du, X Shi, Q Fu, X Ma, H Liu, S Han, D Zhang Proceedings of the ACM Web Conference 2022, 1550-1558, 2022 | 72 | 2022 |
| DANE: Domain Adaptive Network Embedding Y Zhang, G Song, L Du, S Yang, Y Jin IJCAI, 4362-4368, 2019 | 68 | 2019 |
| On the evaluation of neural code summarization E Shi, Y Wang, L Du, J Chen, S Han, H Zhang, D Zhang, H Sun Proceedings of the 44th international conference on software engineering …, 2022 | 64 | 2022 |
| Galaxy Network Embedding: A Hierarchical Community Structure Preserving Approach. L Du, Z Lu, Y Wang, G Song, Y Wang, W Chen IJCAI, 2079-2085, 2018 | 58 | 2018 |
| CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees E Shi, Y Wang, L Du, H Zhang, S Han, D Zhang, H Sun The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 | 55 | 2021 |
| TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data L Du, F Gao, X Chen, R Jia, J Wang, J Zhang, S Han, D Zhang ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021 | 55 | 2021 |
| Gpt4graph: Can large language models understand graph structured data? an empirical evaluation and benchmarking J Guo, L Du, H Liu arXiv preprint arXiv:2305.15066, 2023 | 54 | 2023 |
| On the Evaluation of Commit Message Generation Models: An Experimental Study W Tao, Y Wang, E Shi, L Du, H Zhang, D Zhang, W Zhang IEEE International Conference on Software Maintenance and Evolution (ICSME), 2021 | 38 | 2021 |
| Hierarchical community structure preserving network embedding: A subspace approach L Du, Q Long, Y Wang, G Song, Y Jin, W Lin ACM International Conference on Information and Knowledge Management, 409-418, 2019 | 33 | 2019 |
| TSSRGCN: Temporal Spectral Spatial Retrieval Graph Convolutional Network for Traffic Flow Forecasting X Chen, Y Zhang, L Du, Z Fang, Y Ren, K Bian, K Xie IEEE International Conference on Data Mining (ICDM), 2020 | 32 | 2020 |
| Is a Single Model Enough? MuCoS: A Multi-Model Ensemble Learning Approach for Semantic Code Search L Du, X Shi, Y Wang, E Shi, S Han, D Zhang ACM International Conference on Information & Knowledge Management (CIKM …, 2021 | 30 | 2021 |
| CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network Y Wang, E Shi, L Du, X Yang, Y Hu, S Han, H Zhang, D Zhang arXiv preprint arXiv:2107.01933, 2021 | 29 | 2021 |
| Domain Adaptive Classification on Heterogeneous Information Networks S Yang, G Song, Y Jin, L Du IJCAI, 1410-1416, 2020 | 26 | 2020 |
| Trajgat: A graph-based long-term dependency modeling approach for trajectory similarity computation D Yao, H Hu, L Du, G Cong, S Han, J Bi Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 24 | 2022 |
| Traffic events oriented dynamic traffic assignment model for expressway network: a network flow approach L Du, G Song, Y Wang, J Huang, M Ruan, Z Yu IEEE Intelligent Transportation Systems Magazine 10 (1), 107-120, 2018 | 24 | 2018 |
| Make heterophily graphs better fit gnn: A graph rewiring approach W Bi, L Du, Q Fu, Y Wang, S Han, D Zhang arXiv preprint arXiv:2209.08264, 2022 | 23 | 2022 |
| Race: Retrieval-augmented commit message generation E Shi, Y Wang, W Tao, L Du, H Zhang, S Han, D Zhang, H Sun arXiv preprint arXiv:2203.02700, 2022 | 23 | 2022 |
| Source free unsupervised graph domain adaptation H Mao, L Du, Y Zheng, Q Fu, Z Li, X Chen, S Han, D Zhang arXiv preprint arXiv:2112.00955, 2021 | 21 | 2021 |
| CoCoGUM: Contextual Code Summarization with Multi-Relational GNN on UMLs Y Wang, L Du, E Shi, Y Hu, S Han, D Zhang https://www.microsoft.com/en-us/research/publication/cocogum-contextual-code …, 2020 | 20 | 2020 |
Shi HanMicrosoft Research AsiaVerified email at microsoft.com
