| 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 | 687 | 2020 |
| OFA: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework P Wang, A Yang, R Men, J Lin, S Bai, Z Li, J Ma, C Zhou, J Zhou, H Yang ICML, 2022, 2022 | 559 | 2022 |
| 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 | 397 | 2021 |
| 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 | 391 | 2019 |
| AliGraph: A comprehensive graph neural network platform R Zhu, K Zhao, H Yang, W Lin, C Zhou, B Ai, Y Li, J Zhou 45th International Conference on Very Large Data Bases (VLDB), 2019 | 334* | 2019 |
| Cognitive graph for multi-hop reading comprehension at scale M Ding, C Zhou, Q Chen, H Yang, J Tang Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 253 | 2019 |
| Learning disentangled representations for recommendation J Ma, C Zhou, P Cui, H Yang, W Zhu Neural Information Processing Systems (NeurIPS), 2019., 2019 | 244 | 2019 |
| ANRL: attributed network representation learning via deep neural networks. Z Zhang, H Yang, J Bu, S Zhou, P Yu, J Zhang, M Ester, C Wang Ijcai 18, 3155-3161, 2018 | 239 | 2018 |
| M6: A chinese multimodal pretrainer J Lin, R Men, A Yang, C Zhou, M Ding, Y Zhang, P Wang, A Wang, ... KDD 2021, 2021 | 198* | 2021 |
| Towards Knowledge-Based Recommender Dialog System JT Qibin Chen, Junyang Lin, Yichang Zhang, Ming Ding, Yukuo Cen, Hongxia Yang Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 185* | 2019 |
| Controllable Multi-Interest Framework for Recommendation Y Cen, J Zhang, X Zou, C Zhou, H Yang, J Tang 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 | 179 | 2020 |
| Disentangled self-supervision in sequential recommenders J Ma, C Zhou, H Yang, P Cui, X Wang, W Zhu Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 155 | 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 | 151 | 2022 |
| Understanding Negative Sampling in Graph Representation Learning Z Yang, M Ding, C Zhou, H Yang, J Zhou, J Tang 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2020 | 137 | 2020 |
| Cogltx: Applying bert to long texts M Ding, C Zhou, H Yang, J Tang Advances in Neural Information Processing Systems 33, 12792-12804, 2020 | 118 | 2020 |
| Contrastive Learning for Debiased Candidate Generation in Large-Scale Recommender Systems C Zhou, J Ma, J Zhang, J Zhou, H Yang KDD 2021, 2020 | 101 | 2020 |
| Sequential scenario-specific meta learner for online recommendation Z Du, X Wang, H Yang, J Zhou, J Tang Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 100 | 2019 |
| Sparse-interest network for sequential recommendation Q Tan, J Zhang, J Yao, N Liu, J Zhou, H Yang, X Hu Proceedings of the 14th ACM international conference on web search and data …, 2021 | 92 | 2021 |
| Dependent hierarchical beta process for image interpolation and denoising M Zhou, H Yang, G Sapiro, D Dunson, L Carin Proceedings of the Fourteenth International Conference on Artificial …, 2011 | 90 | 2011 |
| Is a single vector enough? exploring node polysemy for network embedding N Liu, Q Tan, Y Li, H Yang, J Zhou, X Hu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 87 | 2019 |
Jingren ZhouAlibaba Group, MicrosoftVerified email at alibaba-inc.com
