| Arnetminer: extraction and mining of academic social networks J Tang, J Zhang, L Yao, J Li, L Zhang, Z Su Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008 | 2860 | 2008 |
| Self-supervised Learning: Generative or Contrastive X Liu, F Zhang, Z Hou, Z Wang, L Mian, J Zhang, J Tang IEEE Transactions on Knowledge and Data Engineering, 2021 | 2107 | 2021 |
| GPT understands, too X Liu, Y Zheng, Z Du, M Ding, Y Qian, Z Yang, J Tang AI Open, 2023 | 1709* | 2023 |
| GLM: General Language Model Pretraining with Autoregressive Blank Infilling Z Du, Y Qian, X Liu, M Ding, J Qiu, Z Yang, J Tang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 1564 | 2022 |
| P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks X Liu, K Ji, Y Fu, W Tam, Z Du, Z Yang, J Tang Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022 | 1390* | 2022 |
| Social influence analysis in large-scale networks J Tang, J Sun, C Wang, Z Yang Proceedings of the 15th ACM SIGKDD international conference on Knowledge …, 2009 | 1361 | 2009 |
| 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 Eleventh ACM International Conference on Web Search and …, 2018 | 1116 | 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 | 1042 | 2020 |
| Pre-trained models: Past, present and future X Han, Z Zhang, N Ding, Y Gu, X Liu, Y Huo, J Qiu, Y Yao, A Zhang, ... AI Open 2, 225-250, 2021 | 944 | 2021 |
| Cogview: Mastering text-to-image generation via transformers M Ding, Z Yang, W Hong, W Zheng, C Zhou, D Yin, J Lin, X Zou, Z Shao, ... Advances in Neural Information Processing Systems 34, 19822-19835, 2021 | 805 | 2021 |
| 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 | 682 | 2018 |
| Parameter-efficient fine-tuning of large-scale pre-trained language models N Ding, Y Qin, G Yang, F Wei, Z Yang, Y Su, S Hu, Y Chen, CM Chan, ... Nature Machine Intelligence 5 (3), 220-235, 2023 | 681 | 2023 |
| 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, ... ICLR‘23, 2023 | 609 | 2023 |
| RiMOM: A dynamic multistrategy ontology alignment framework J Li, J Tang, Y Li, Q Luo IEEE Transactions on Knowledge and data Engineering 21 (8), 1218-1232, 2008 | 609 | 2008 |
| User-level sentiment analysis incorporating social networks C Tan, L Lee, J Tang, L Jiang, M Zhou, P Li Proceedings of the seventeenth ACM SIGKDD international conference on …, 2011 | 595 | 2011 |
| GraphMAE: Self-Supervised Masked Graph Autoencoders Z Hou, X Liu, Y Dong, C Wang, J Tang Proceedings of the Twenty-Eighth ACM SIGKDD International Conference on …, 2022 | 585 | 2022 |
| 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 | 572 | 2023 |
| Representation learning for attributed multiplex heterogeneous network Y Cen, X Zou, J Zhang, H Yang, J Zhou, J Tang Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 502 | 2019 |
| Cogvideo: Large-scale pretraining for text-to-video generation via transformers W Hong, M Ding, W Zheng, X Liu, J Tang ICLR‘23, 2023 | 493 | 2023 |
| 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, 22092-22103, 2020 | 450 | 2020 |
Juanzi LiTsinghua UniversityVerified email at tsinghua.edu.cn
