Wentao Zhang

Wentao Zhang

北京大学 助理教授/研究员/博导

Publications

* indicates equal contribution, # indicates corresponding author 2025 ====

  1. Training-free Heterogeneous Graph Condensation via Data Selection.
    Yuxuan Liang, Wentao Zhang#, Xinyi Gao, Ling Yang, Chong Chen, Hongzhi Yin, Yunhai Tong, Bin Cui
    ICDE 2025, CCF-A<.

  2. Towards Scalable and Efficient Graph Structure Learning.
    Siqi Shen, Wentao Zhang#, Chengshuo Du, Chong Chen, Fangcheng Fu, Yingxia Shao, Bin Cui
    ICDE 2025, CCF-A.

  3. Towards Scalable and Deep Graph Neural Networks via Noise Masking.
    Yuxuan Liang, Wentao Zhang#, Zeang Sheng, Ling Yang, Quanqing Xu, Jiawei Jiang, Yunhai Tong, Bin CUI
    AAAI 2025, CCF-A.

  4. FedVCK: Non-IID Robust and Communication-Efficient Federated Learning via Valuable Condensed Knowledge for Medical Image Analysis.
    Guochen Yan, Luyuan Xie, Xinyi Gao, Wentao Zhang, Qingni Shen, Yuejian Fang, Zhonghai Wu
    AAAI 2025, CCF-A.

2024

  1. Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models.
    Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E. Gonzalez, Bin CUI
    NeurIPS 2024, CCF-A.

  2. Efficient Multi-task LLM Quantization and Serving for Multiple LoRA Adapters.
    Yifei Xia, Fangcheng Fu, Wentao Zhang, Jiawei Jiang, Bin CUI.
    NeurIPS 2024, CCF-A.

  3. Distribution-Aware Data Expansion with Diffusion Models.
    haoweiz, Ling Yang, Jun-Hai Yong, Hongzhi Yin, Jiawei Jiang, Meng Xiao, Wentao Zhang#, Bin Wang
    NeurIPS 2024, CCF-A.

  4. MetaGXplore: Integrating Multi-Omics Data with Graph Convolutional Networks for Pan-cancer Patient Metastasis Identification.
    Tao Jiang, Haiyang Jiang, Xinyi Ma, Minghao Xu, Yan Liang, and Wentao Zhang#.
    IEEE BIBM 2024, CCF-B.

  5. Physics-guided Active Sample Reweighting for Urban Flow Prediction.
    Wei Jiang, Tong Chen, Guanhua Ye, Wentao Zhang, Lizhen Cui, Zi Huang and Hongzhi Yin.
    ***CIKM 2024, CCF-B, 🏆 Best Student Paper Award (among 1496 submmisions)***.

  6. ProtLLM: An Interleaved Protein-Language LLM with Protein-as-Word Pre-Training.
    Le Zhuo, Zewen Chi, Minghao Xu, Heyan Huang, Jianan Zhao, Heqi Zheng, Conghui He, Xian-Ling Mao, Wentao Zhang#.
    ACL (main) 2024, CCF-A.

  7. Diffusion Models: A Comprehensive Survey of Methods [Paper][Code]
    Ling Yang, Zhilong Zhang, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang#, Ming-Hsuan Yang#, Bin Cui#.
    CSUR 2024, CCF-A.

  8. OUTRE: An OUT-of-core De-REdundancy GNN Training Framework for Massive Graphs within A Single Machine.
    Zeang Sheng, Wentao Zhang, Yangyu Tao, Bin Cui#.
    VLDB 2024, CCF-A.

  9. HGAMLP: Heterogeneous Graph Attention MLP with De-redundancy Mechanism.
    Yuxuan Liang, Wentao Zhang#, Zeang Sheng, Ling Yang, Jiawei Jiang, Yunhai Tong, Bin Cui.
    ICDE 2024, CCF-A.

  10. NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention.
    Wentao Zhang, Guochen Yan , Yu Shen , Yang Ling , Yangyu Tao , Bin Cui , Jian Tang
    SIGMOD 2024, CCF-A.

  11. BIM: Improving Graph Neural Networks with Balanced Influence Maximization.
    Wentao Zhang, Xinyi Gao, Ling Yang, Meng Cao, Jiulong Shan, Hongzhi Yin, Bin Cui.
    ICDE 2024, CCF-A.

  12. NC-ALG: Graph-based Active Learning under Noisy Crowd.
    Wentao Zhang, Yexin Wang, Zhenbang You, Yang Li, Gang Cao, Zhi Yang, Bin Cui.
    ICDE 2024, CCF-A.

  13. Graph Condensation for Open-World Graph Learning.
    Xinyi Gao, Tong Chen, Wentao Zhang, Yayong Li, Xiangguo Sun, Hongzhi Yin.
    SIGKDD 2024, CCF-A.

  14. Rethinking Node-wise Propagation for Large-scale Graph Learning.
    Xunkai Li, Jingyuan Ma, Zhengyu Wu, Daohan Su, Wentao Zhang, Rong-Hua Li, Guoren Wang
    WWW 2024, CCF-A.

  15. FedGTA: Topology-aware Averaging for Federated Graph Learning.
    Xunkai Li, Zhengyu Wu, Wentao Zhang, Yinlin Zhu, Rong-Hua Li, Guoren Wang
    VLDB 2024, CCF-A.

  16. Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation.
    Xinyi Gao, Wentao Zhang#, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin #.
    ICDE 2024, CCF-A.

  17. Graph Condensation for Inductive Node Representation Learning.
    Xinyi Gao, Tong Chen, Yiling Zang, Wentao Zhang, Quoc Viet Hung Nguyen, Kai Zheng, Hongzhi Yin.
    ICDE 2024, CCF-A.

  18. AdaFGL: A New Paradigm for Federated Node Classification with Topology Heterogeneity.
    Xunkai Li, Zhenyu Wu, Wentao Zhang, Henan Sun, Ronghua Li, Guoren Wang.
    ICDE 2024, CCF-A.

  19. Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning.
    Yuxiang Wang, Xiao Yan, Chuang Hu, Quanqing Xu, Chuanhui Yang, Fangcheng Fu, Wentao Zhang, Hao Wang , Bo Du, Jiawei Jiang.
    ICDE 2024, CCF-A.

  20. Multi-View Teacher with Curriculum Data Fusion for Robust Unsupervised Domain Adaptation.
    Yuhao Tang, Junyu Luo, Ling Yang, Xiao Luo, Wentao Zhang, Bin Cui.
    ICDE 2024, CCF-A.

  21. Graphusion: Latent Diffusion for Graph Generation.
    Ling Yang, Zhilin Huang, Zhilong Zhang, Zhongyi Liu, Shenda Hong, Wentao Zhang, Wenming Yang, Bin Cui, Luxia Zhang.
    TKDE 2024, CCF-A.

  22. OpenBox: A Python Toolkit for Generalized Black-box Optimization.
    Huaijun Jiang, Yu Shen, Yang Li, Beicheng Xu, Sixian Du, Wentao Zhang, Ce Zhang, Bin Cui.
    JMLR 2024, CCF-A.

  23. Interaction-based Retrieval-augmented Diffusion Models for Protein-specific 3D Molecule Generation.
    Zhilin Huang, Ling Yang, Xiangxin Zhou, Chujun Qin, Yijie Yu, Xiawu Zheng, Zikun Zhou, Wentao Zhang, Yu Wang, Wenming Yang.
    ICML 2024, CCF-A.

  24. Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models. [To appear]
    Zhilin Huang, Ling Yang, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang, Bin Cui, Wenming Yang
    ICLR 2024.

  25. VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs.
    Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec
    ICLR 2024.

  26. Towards Effective and General Graph Unlearning via Mutual Evolution.
    Xunkai Li, Yulin Zhao, Zhengyu Wu, Wentao Zhang, Ronghua Li, Guoren Wang.
    AAAI 2024, CCF-A.

2023

  1. Improving Diffusion-Based Image Synthesis with Context Prediction.
    Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang#, Bin Cui#.
    NeurIPS 2023, CCF-A.

  2. Diffusion Models: A Comprehensive Survey of Methods.
    Ling Yang, Zhilong Zhang, …, Wentao Zhang#, Bin Cui#, Ming-Hsuan Yang#.
    ACM Computing Survey.
    CSUR 2023, CCF-A.

  3. FedGTA: Topology-aware Averaging for Federated Graph Learning.
    Xunkai Li, Zhenyu Wu, Wentao Zhang, Yinlin Zhu, Ronghua Li, Guoren Wang.
    International Conference on Very Large Data Bases.
    VLDB 2023, CCF-A.

  4. Rover: An online Spark SQL tuning service via generalized transfer learning.
    Yu Shen, Xinyuyang Ren, Yupeng Lu, Huaijun Jiang, Di Peng, Huanyong Xu, Yang Li, Wentao Zhang#, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2023, CCF-A.

  5. Towards General and Efficient Online Tuning for Spark.
    Yang Li, Huanjun Jiang, …, Wentao Zhang, Ce Zhang, Peng Chen, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2023, CCF-A.

  6. Scapin : Scalable Graph Perturbation by Augmented Influence Maximization.
    Yexin Wang, Zhi Yang, Junqi Liu, Wentao Zhang, Bin Cui.
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2023, CCF-A.

  7. Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization.
    Ling Yang, Jiayi Zheng, Heyuan Wang, Zhongyi Liu, Zhilin Huang, Shenda Hong, Wentao Zhang#, Bin Cui.
    IEEE Transactions on Knowledge and Data Engineering.
    TKDE 2023, CCF-A.

  8. ProxyBO: Accelerating Neural Architecture Search via Bayesian Optimization with Zero-cost Proxies. [Paper]
    Yu Shen, Yang Li, Jian Zheng, Peng Yao, Jixiang Li, Sen Yang, Ji Liu, Wentao Zhang#, Bin Cui.
    Thirty-Seventh AAAI Conference on Artificial Intelligence.
    AAAI 2023, CCF-A.

  9. Fairness-aware Maximal Biclique Enumeration on Bipartite Graphs. [Paper]
    Ziqi Yin, Qi Zhang, Wentao Zhang, Ronghua Li, Guoren Wang
    IEEE International Conference on Data Engineering.
    ICDE 2023, CCF-A.

  10. Semantic-aware Node Synthesis for Imbalanced Heterogeneous Information Networks. [To appear]
    Xinyi Gao, Wentao Zhang, Tong Chen, Junliang Yu, Quoc Viet Hung Nguyen and Hongzhi Yin
    ACM International Conference on Information and Knowledge Management.
    CIKM 2023, CCF-B.

  11. Graph-Enforced Neural Network for Attributed Graph Clustering. [To appear]
    Zeang Sheng, Wentao Zhang#, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang and Bin Cui
    The 7th APWeb-WAIM International Joint Conference on Web and Big Data.
    APWeb-WAIM2023, CCF-C, 🏆 Best Paper Runner Up Award (among 260 submmisions).

2022

  1. NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning. [Paper][Code]
    Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui.
    The 39th International Conference on Machine Learning.
    ICML 2022, CCF-A.

  2. Deep and Flexible Graph Neural Architecture Search. [Paper][Code]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Zhi Yang, Bin Cui.
    The 39th International Conference on Machine Learning.
    ICML 2022, CCF-A.

  3. Model Degradation Hinders Deep Graph Neural Networks. [Paper][Code]
    Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  4. Graph Attention Multi-Layer Perceptron. [Paper][Code]
    Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  5. PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm. [Paper][Code] [Doc]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang,Yangyu Tao, Zhi Yang, Bin Cui.
    The Web Conference.
    WWW 2022 (System Track), CCF-A, 🏆 Best Student Paper Award (among 1822 submmisions).

  6. Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels . [Paper][Code]
    Wentao Zhang, Yexin Wang, Zhenbang You, …, Zhi Yang, Bin Cui.
    International Conference on Learning Representations.
    ICLR 2022.

  7. Graph Neural Networks in Recommender Systems: A Survey [Paper][Code]
    Shiwen Wu, Fei Sun, Wentao Zhang#, Xu Xie, Bin Cui.
    ACM Computing Surveys.
    CSUR 2022, CCF-A.

  8. P2CG: A Privacy Preserving Collaborative Graph Neural Network Training Framework.* [Paper]
    Xupeng Miao*, Wentao Zhang*, …, Lei Chen, Yangyu Tao, Gang Cao, Bin Cui.
    The International Journal on Very Large Data Bases.
    VLDBJ 2022, CCF-A.

  9. DivBO: Diversity-aware CASH for Ensemble Learning [Paper]
    Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, Bin CUI.
    NeurIPS 2022, CCF-A.

  10. TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning. [Paper]
    Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  11. Transfer Learning based Search Space Design for Hyperparameter Tuning. [Paper]
    Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2022, CCF-A.

  12. Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale. [Paper][Code]
    Yang Li, Yu Shen, Huaijun Jiang,Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2022, CCF-A.

  13. Zoomer: Improving and Accelerating Recommendation on Web-Scale Graphs via Regions of Interests. [Paper][Code]
    Yuezihan Jiang, Yu Cheng, Hanyu Zhao, Wentao Zhang, Xupeng Miao, Yu He, Liang Wang, Zhi Yang, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE 2022 (Industry Track), CCF-A.

  14. Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture [Paper][Code]
    Xupeng Miao*, Wentao Zhang*, Yingxia Shao, Lei Chen, Ce Zhang, Jiawei Jiang, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE (Extended Abstract) 2022, CCF-A.

  15. Efficient End-to-End AutoML via Scalable Search Space Decomposition. [Paper][Code[Doc]]
    Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui.
    The International Journal on Very Large Data Bases.
    VLDBJ 2022, CCF-A.

  16. AutoDC: an Automatic Machine Learning Framework for Disease Classification [Paper]
    Yang Bai, Yang Li, Yu Shen, Mingyu Yang, Wentao Zhang, Bin Cui.
    Bioinformatics.
    Bioinformatics 2022, CCF-B.

  17. K-Core Decomposition on Super Large Graphs with Limited Resources [Paper]
    Shicheng Gao, Jie Xu, Xiaosen Li, Fangcheng Fu, Wentao Zhang, Wen Ouyang, Yangyu Tao and Bin Cui.
    The 37th ACM/SIGAPP Symposium On Applied Computing.
    ACM SAC 2022.

2021

  1. RIM: Reliable Influence-based Active Learning on Graphs [Paper][Code]
    Wentao Zhang, Yexin Wang, Zhenbang You, Meng Cao, Ping Huang, Jiulong Shan, Zhi Yang, Bin Cui.
    Thirty-fifth Conference on Neural Information Processing Systems.
    NeurIPS 2021, CCF-A, Spotlight Presentation, Acceptance Rate: < 3%.

  2. Node Dependent Local Smoothing for Scalable Graph Learning [Paper][Code]
    Wentao Zhang, Mingyu Yang, Zeang Sheng, Yang Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui.
    Thirty-fifth Conference on Neural Information Processing Systems.
    NeurIPS 2021, CCF-A, Spotlight Presentation, Acceptance Rate: < 3%.

  3. Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization [Paper][Code]
    Wentao Zhang, Zhi Yang, Yexin Wang, Yu Shen, Yang Li, Liang Wang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2021, CCF-A.

  4. Lasagne: A Multi-Layer Graph Convolutional Network Framework via Node-aware Deep Architecture [Paper][Code]
    Xupeng Miao*, Wentao Zhang*, Yingxia Shao, Lei Chen, Ce Zhang, Jiawei Jiang, Bin Cui.
    IEEE Transactions on Knowledge and Data Engineering.
    TKDE 2021, CCF-A.

  5. DeGNN: Characterizing and Improving Graph Neural Networks with Graph Decomposition [Paper][Code]
    Xupeng Miao*, Nezihe Merve Gürel*, Wentao Zhang*, …, Shuai Zhang, Yujing Wang, Bin Cui, Ce Zhang.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining.

  6. ROD: Reception-aware Online Distillation for Sparse Graphs [Paper][Code]
    Wentao Zhang, Jiang Yuezihan, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining .

  7. ALG: Fast and Accurate Active Learning Framework for Graph Convolutional Networks [Paper][Code]
    Wentao Zhang, Yu Shen, Yangli, Lei Chen, Zhi Yang, Bin Cui
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2021, CCF-A, Top #1 conference in Data Bases.

  8. Distributed Optimization and Implementation of Graph Embedding Algorithms [Paper][Code]
    Wentao Zhang, Bin Yuan, ZhiPeng Zhang, Bin Cui.
    Journal of Software.
    JOS 2021, CCF-A.

  9. VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition [Paper][Code[Doc]]
    Yang Li, Yu Shen, Wentao Zhang, …, Wentao Wu, Ce Zhang, Bin Cui.
    International Conference on Very Large Data Bases.
    VLDB 2021, CCF-A.

  10. OpenBox: A Generalized Black-box Optimization Service [Paper][Code][Doc]
    Yang Li, Yu Shen, Wentao Zhang, …, Ce Zhang, Bin Cui.
    SIGKDD Conference on Knowledge Discovery and Data Mining.
    SIGKDD 2021, CCF-A, Top #1 conference in Data Mining.

  11. Enhanced review-based rating prediction by exploiting aside information and user influence [Paper][Code]
    Shiwen Wu, Yuanxing Zhang, Wentao Zhang, Kaigui Bian, Bin Cui.
    Knowledge Based System.
    KBS 2021, JCR Q1, IF=8.038.

2020

  1. Reliable Data Distillation on Graph Convolutional Network [Paper][Code]
    Wentao Zhang*, Xupeng Miao*, Yingxia Shao, Jiawei Jiang, Lei Chen, Olivier Ruas, Bin Cui
    ACM SIGMOD International Conference on Management of Data.
    SIGMOD 2020, CCF-A, Top #1 conference in Data Bases.

  2. Efficient Diversity-Driven Ensemble for Deep Neural Networks [Paper][Code]
    Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui.
    IEEE International Conference on Data Engineering.
    ICDE 2020, CCF-A.

  3. Snapshot Boosting: A Fast Ensemble Framework for Deep Neural Networks [Paper][Code]
    Wentao Zhang, Jiawei Jiang, Yingxia Shao, Bin Cui.
    Sci China Inf Sci.
    SCIS 2020, CCF-A.

Preprints

  1. Distributed Graph Neural Network Training: A Survey [Paper]
    Yingxia Shao, Hongzheng Li, Xizhi Gu, Hongbo Yin, Yawen Li, Xupeng Miao, Wentao Zhang, Bin Cui, Lei Chen.
    arXiv:2211.00216, 2022. (arXiv preprint).

  2. Efficient Graph Neural Network Inference at Large Scale [Paper]
    Xinyi Gao, Wentao Zhang#, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin.
    arXiv:2211.00495, 2022. (arXiv preprint).

  3. Diffusion Models: A Comprehensive Survey of Methods [Paper][Code]
    Ling Yang, Zhilong Zhang, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang#, Ming-Hsuan Yang, Bin Cui.
    arXiv:2209.00796, 2022. (arXiv preprint).

  4. Evaluating Deep Graph Neural Networks [Paper][Code]
    Wentao Zhang, Zeang Sheng, Yuezihan Jiang, Yikuan Xia, Jun Gao, Zhi Yang, Bin Cui.
    arXiv:2011.02260, 2020. (arXiv preprint).

  5. Graph Attention Multi-Layer Perceptron [Paper][Code]
    Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui.
    arXiv:2108.10097, 2021. (arXiv preprint).

  6. GMLP: Building Scalable and Flexible Graph Neural Networks with Feature-Message Passing [Paper][Code]
    Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui.
    arXiv:2108.00955, 2021. (arXiv preprint).