| Fairness-aware explainable recommendation over knowledge graphs Z Fu, Y Xian, R Gao, J Zhao, Q Huang, Y Ge, S Xu, S Geng, C Shah, ... Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 81 | 2020 |
| Counterfactual explainable recommendation J Tan, S Xu, Y Ge, Y Li, X Chen, Y Zhang Proceedings of the 30th ACM International Conference on Information …, 2021 | 21 | 2021 |
| Towards personalized fairness based on causal notion Y Li, H Chen, S Xu, Y Ge, Y Zhang Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 17 | 2021 |
| Causal collaborative filtering S Xu, Y Ge, Y Li, Z Fu, X Chen, Y Zhang arXiv preprint arXiv:2102.01868, 2021 | 16 | 2021 |
| Learning Personalized Risk Preferences for Recommendation Y Ge, S Xu, S Liu, Z Fu, F Sun, Y Zhang Proceedings of the 43rd International ACM SIGIR Conference on Research and …, 2020 | 15 | 2020 |
| Maximizing marginal utility per dollar for economic recommendation Y Ge, S Xu, S Liu, S Geng, Z Fu, Y Zhang The World Wide Web Conference, 2757-2763, 2019 | 14 | 2019 |
| Learning post-hoc causal explanations for recommendation S Xu, Y Li, S Liu, Z Fu, X Chen, Y Zhang arXiv preprint arXiv:2006.16977, 2020 | 11 | 2020 |
| HOOPS: Human-in-the-Loop Graph Reasoning for Conversational Recommendation Z Fu, Y Xian, Y Zhu, S Xu, Z Li, G De Melo, Y Zhang Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 10 | 2021 |
| Learning causal explanations for recommendation S Xu, Y Li, S Liu, Z Fu, Y Ge, X Chen, Y Zhang The 1st International Workshop on Causality in Search and Recommendation, 2021 | 7 | 2021 |
| Learning and evaluating graph neural network explanations based on counterfactual and factual reasoning J Tan, S Geng, Z Fu, Y Ge, S Xu, Y Li, Y Zhang Proceedings of the ACM Web Conference 2022, 1018-1027, 2022 | 5 | 2022 |
| Efficient Non-Sampling Knowledge Graph Embedding Z Li, J Ji, Z Fu, Y Ge, S Xu, C Chen, Y Zhang Proceedings of the Web Conference 2021, 1727-1736, 2021 | 5 | 2021 |
| HID: hierarchical multiscale representation learning for information diffusion H Zhou, S Xu, Z Fu, G De Melo, Y Zhang, M Kapadia International Joint Conference on Artificial Intelligence, 2020 | 5 | 2020 |
| FedCT: Federated Collaborative Transfer for Recommendation S Liu, S Xu, W Yu, Z Fu, Y Zhang, A Marian Proceedings of the 44th International ACM SIGIR Conference on Research and …, 2021 | 4 | 2021 |
| Discrete knowledge graph embedding based on discrete optimization Y Li, S Xu, B Liu, Z Fu, S Liu, X Chen, Y Zhang arXiv preprint arXiv:2101.04817, 2021 | 3 | 2021 |
| Deconfounded Causal Collaborative Filtering S Xu, J Tan, S Heinecke, J Li, Y Zhang arXiv preprint arXiv:2110.07122, 2021 | 2 | 2021 |
| Counterfactual Evaluation for Explainable AI Y Ge, S Liu, Z Li, S Xu, S Geng, Y Li, J Tan, F Sun, Y Zhang arXiv preprint arXiv:2109.01962, 2021 | | 2021 |
| Personalized Counterfactual Fairness in Recommendation Y Li, H Chen, S Xu, Y Ge, Y Zhang arXiv preprint arXiv:2105.09829, 2021 | | 2021 |
