| Diffusion models: A comprehensive survey of methods and applications L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, Y Shao, W Zhang*, ... ACM Computing Surveys, 2022 | 1682 | 2022 |
| Graph neural networks in recommender systems: a survey S Wu, F Sun, W Zhang*, X Xie, B Cui* ACM Computing Surveys 55 (5), 1-37, 2022 | 1450 | 2022 |
| Retrieval-augmented generation for ai-generated content: A survey P Zhao, H Zhang, Q Yu, Z Wang, Y Geng, F Fu, L Yang, W Zhang, J Jiang, ... arXiv preprint arXiv:2402.19473, 2024 | 216 | 2024 |
| Graph attention multi-layer perceptron W Zhang, Z Yin, Z Sheng, Y Li, W Ouyang, X Li, Y Tao, Z Yang, B Cui ACM SIGKDD 2022, 2022 | 153* | 2022 |
| Model Degradation Hinders Deep Graph Neural Networks W Zhang, Z Sheng, Z Yin, Y Jiang, Y Xia, J Gao, Z Yang, B Cui ACM SIGKDD 2022, 2022 | 92* | 2022 |
| Reliable data distillation on graph convolutional network W Zhang, X Miao, Y Shao, J Jiang, L Chen, O Ruas, B Cui ACM SIGMOD 2020, 1399-1414, 2020 | 91 | 2020 |
| OpenBox: A Generalized Black-box Optimization Service Y Li, Y Shen, W Zhang, Y Chen, H Jiang, M Liu, J Jiang, J Gao, W Wu, ... ACM SIGKDD 2021, 2021 | 82 | 2021 |
| Node Dependent Local Smoothing for Scalable Graph Learning W Zhang, M Yang, Z Sheng, Y Li, W Ouyang, Y Tao, Z Yang, B Cui NeurIPS 2021, Spotlight Paper (Acceptance Rate < 3%), 2021 | 71 | 2021 |
| Snapshot boosting: a fast ensemble framework for deep neural networks W Zhang, J Jiang, Y Shao, B Cui Science China Information Sciences 63 (1), 112102, 2020 | 69 | 2020 |
| Distributed graph neural network training: A survey Y Shao, H Li, X Gu, H Yin, Y Li, X Miao, W Zhang, B Cui, L Chen ACM Computing Surveys 56 (8), 1-39, 2024 | 64 | 2024 |
| PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm W Zhang, Y Shen, Z Lin, Y Li, X Li, W Ouyang, Y Tao, Z Yang, B Cui WWW 2022, Best Student Paper Award, 2022 | 59 | 2022 |
| VolcanoML: speeding up end-to-end AutoML via scalable search space decomposition Y Li, Y Shen, W Zhang, C Zhang, B Cui The VLDB Journal 32 (2), 389-413, 2023 | 56 | 2023 |
| Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization W Zhang, Z Yang, Y Wang, Y Shen, Y Li, L Wang, B Cui VLDB 2021, 2021 | 55 | 2021 |
| Deepseek-coder: When the large language model meets programming–the rise of code intelligence, 2024 D Guo, Q Zhu, D Yang, Z Xie, K Dong, W Zhang, G Chen, X Bi, Y Wu, ... URL https://arxiv. org/abs/2401.14196 5, 19, 2024 | 50 | 2024 |
| DeGNN: Improving Graph Neural Networks with Graph Decomposition X Miao, NM Gürel, W Zhang, Z Han, B Li, W Min, SX Rao, H Ren, Y Shan, ... ACM SIGKDD 2021, 1223-1233, 2021 | 45* | 2021 |
| Alg: Fast and accurate active learning framework for graph convolutional networks W Zhang, Y Shen, Y Li, L Chen, Z Yang, B Cui ACM SIGMOD 2021, 2366-2374, 2021 | 45 | 2021 |
| Diffusion-based scene graph to image generation with masked contrastive pre-training L Yang, Z Huang, Y Song, S Hong, G Li, W Zhang, B Cui, B Ghanem, ... arXiv preprint arXiv:2211.11138, 2022 | 43 | 2022 |
| A survey of multimodal large language model from a data-centric perspective T Bai, H Liang, B Wan, Y Xu, X Li, S Li, L Yang, B Li, Y Wang, B Cui, ... arXiv preprint arXiv:2405.16640, 2024 | 42 | 2024 |
| Transfer learning for bayesian optimization: A survey T Bai, Y Li, Y Shen, X Zhang, W Zhang, B Cui arXiv preprint arXiv:2302.05927, 2023 | 41 | 2023 |
| Lasagne: A multi-layer graph convolutional network framework via node-aware deep architecture X Miao, W Zhang, Y Shao, B Cui, L Chen, C Zhang, J Jiang IEEE Transactions on Knowledge and Data Engineering 2021, 2021 | 39 | 2021 |
Bin CUIProfessor of Computer Science, Peking UniversityVerified email at pku.edu.cn