Open graph benchmark: Datasets for machine learning on graphs W Hu, M Fey, M Zitnik, Y Dong, H Ren, B Liu, M Catasta, J Leskovec Advances in Neural Information Processing Systems 33, 2020 | 2535 | 2020 |
metapath2vec: Scalable Representation Learning for Heterogeneous Networks Y Dong, NV Chawla, A Swami Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 2474 | 2017 |
Heterogeneous Graph Transformer Z Hu, Y Dong, K Wang, Y Sun Proceedings of The Web Conference 2020, 2704-2710, 2020 | 1152 | 2020 |
Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec J Qiu, Y Dong, H Ma, J Li, K Wang, J Tang Proceedings of the 11th ACM International Conference on Web Search and Data …, 2018 | 1045 | 2018 |
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training J Qiu, Q Chen, Y Dong, J Zhang, H Yang, M Ding, K Wang, J Tang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 878 | 2020 |
Glm-130b: An open bilingual pre-trained model A Zeng, X Liu, Z Du, Z Wang, H Lai, M Ding, Z Yang, Y Xu, W Zheng, X Xia, ... arXiv preprint arXiv:2210.02414, 2022 | 751 | 2022 |
DeepInf: Social Influence Prediction with Deep Learning J Qiu, J Tang, H Ma, Y Dong, K Wang, J Tang Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 592 | 2018 |
GPT-GNN: Generative Pre-Training of Graph Neural Networks Z Hu, Y Dong, K Wang, KW Chang, Y Sun Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 512 | 2020 |
Microsoft Academic Graph: When experts are not enough K Wang, Z Shen, C Huang, CH Wu, Y Dong, A Kanakia Quantitative Science Studies 1 (1), 396-413, 2020 | 492 | 2020 |
Graph Random Neural Networks for Semi-Supervised Learning on Graphs W Feng, J Zhang, Y Dong, Y Han, H Luan, Q Xu, Q Yang, E Kharlamov, ... Advances in Neural Information Processing Systems 33, 2020 | 378 | 2020 |
Graphmae: Self-supervised masked graph autoencoders Z Hou, X Liu, Y Cen, Y Dong, H Yang, C Wang, J Tang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 373 | 2022 |
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs W Hu, M Fey, H Ren, M Nakata, Y Dong, J Leskovec arXiv preprint arXiv:2103.09430, 2021 | 356 | 2021 |
Link prediction and recommendation across heterogeneous social networks Y Dong, J Tang, S Wu, J Tian, NV Chawla, J Rao, H Cao 2012 IEEE 12th International Conference on Data Mining, 181-190, 2012 | 350 | 2012 |
Inferring user demographics and social strategies in mobile social networks Y Dong, Y Yang, J Tang, Y Yang, NV Chawla Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 249 | 2014 |
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks Q Lv, M Ding, Q Liu, Y Chen, W Feng, S He, C Zhou, J Jiang, Y Dong, ... Proceedings of the 27th ACM SIGKDD International Conference on Knowledge …, 2021 | 244 | 2021 |
Cogvlm: Visual expert for pretrained language models W Wang, Q Lv, W Yu, W Hong, J Qi, Y Wang, J Ji, Z Yang, L Zhao, X Song, ... arXiv preprint arXiv:2311.03079, 2023 | 224 | 2023 |
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Benchmarking on HumanEval-X Q Zheng, X Xia, X Zou, Y Dong, S Wang, Y Xue, L Shen, Z Wang, A Wang, ... Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 215* | 2023 |
ProNE: Fast and Scalable Network Representation Learning J Zhang, Y Dong, Y Wang, J Tang, M Ding Proceedings of the Twenty-Eighth International Joint Conference on …, 2019 | 207 | 2019 |
NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization J Qiu, Y Dong, H Ma, J Li, C Wang, K Wang, J Tang The World Wide Web Conference, 1509-1520, 2019 | 200 | 2019 |
Agentbench: Evaluating llms as agents X Liu, H Yu, H Zhang, Y Xu, X Lei, H Lai, Y Gu, H Ding, K Men, K Yang, ... arXiv preprint arXiv:2308.03688, 2023 | 199* | 2023 |