| Mind: A large-scale dataset for news recommendation F Wu, Y Qiao, JH Chen, C Wu, T Qi, J Lian, D Liu, X Xie, J Gao, W Wu, ... ACL 2020, 3597-3606, 2020 | 560 | 2020 |
| A federated graph neural network framework for privacy-preserving personalization C Wu, F Wu, L Lyu, T Qi, Y Huang, X Xie Nature Communications 13 (1), 3091, 2022 | 466* | 2022 |
| Neural news recommendation with multi-head self-attention C Wu, F Wu, S Ge, T Qi, Y Huang, X Xie EMNLP 2019, 6389-6394, 2019 | 399 | 2019 |
| Empowering News Recommendation with Pre-trained Language Models C Wu, F Wu, T Qi, Y Huang SIGIR 2021, 2021 | 185 | 2021 |
| Fastformer: Additive attention can be all you need C Wu, F Wu, T Qi, Y Huang, X Xie arXiv preprint arXiv:2108.09084, 2021 | 174 | 2021 |
| Privacy-Preserving News Recommendation Model Training via Federated Learning T Qi, F Wu, C Wu, Y Huang, X Xie EMNLP:Findings 2020, 2020 | 172* | 2020 |
| Graph enhanced representation learning for news recommendation S Ge, C Wu, F Wu, T Qi, Y Huang WWW 2020, 2863-2869, 2020 | 146 | 2020 |
| Personalized News Recommendation with Knowledge-aware Interactive Matching T Qi, F Wu, C Wu, Y Huang SIGIR 2021, 2021 | 96 | 2021 |
| HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation T Qi, F Wu, C Wu, P Yang, Y Yu, X Xie, Y Huang ACL 2021, 2021 | 94 | 2021 |
| Feedrec: News feed recommendation with various user feedbacks C Wu, F Wu, T Qi, Q Liu, X Tian, J Li, W He, Y Huang, X Xie Proceedings of the ACM Web Conference 2022, 2088-2097, 2022 | 87 | 2022 |
| PP-Rec: News Recommendation with Personalized User Interest and Time-aware News Popularity T Qi, F Wu, C Wu, Y Huang ACL 2021, 2021 | 78 | 2021 |
| Fedner: Privacy-preserving medical named entity recognition with federated learning S Ge, F Wu, C Wu, T Qi, Y Huang, X Xie arXiv preprint arXiv:2003.09288, 2020 | 78 | 2020 |
| User Modeling with Click Preference and Reading Satisfaction for News Recommendation. C Wu, F Wu, T Qi, Y Huang IJCAI 2020, 3023-3029, 2020 | 78 | 2020 |
| Mm-rec: Visiolinguistic model empowered multimodal news recommendation C Wu, F Wu, T Qi, C Zhang, Y Huang, T Xu Proceedings of the 45th international ACM SIGIR conference on research and …, 2022 | 76* | 2022 |
| Hi-Transformer: Hierarchical Interactive Transformer for Efficient and Effective Long Document Modeling C Wu, F Wu, T Qi, Y Huang ACL 2021, 2021 | 70 | 2021 |
| FedAttack: Effective and Covert Poisoning Attack on Federated Recommendation via Hard Sampling C Wu, F Wu, T Qi, Y Huang, X Xie KDD, 2022 | 59 | 2022 |
| Reviews meet graphs: Enhancing user and item representations for recommendation with hierarchical attentive graph neural network C Wu, F Wu, T Qi, S Ge, Y Huang, X Xie EMNLP 2019, 4884-4893, 2019 | 58 | 2019 |
| Neural news recommendation with heterogeneous user behavior C Wu, F Wu, M An, T Qi, J Huang, Y Huang, X Xie EMNLP 2019, 4874-4883, 2019 | 57 | 2019 |
| PTUM: Pre-training User Model from Unlabeled User Behaviors via Self-supervision C Wu, F Wu, T Qi, J Lian, Y Huang, X Xie EMNLP:Findings 2020, 2020 | 55 | 2020 |
| NoisyTune: A Little Noise Can Help You Finetune Pretrained Language Models Better C Wu, F Wu, T Qi, Y Huang, X Xie ACL, 2022 | 54 | 2022 |
Chuhan WuWeChat AI, Tencenttencent.com의 이메일 확인됨
