| Counterfactual Explainable Recommendation J Tan, S Xu, Y Ge, Y Li, Y Zhang The 30th ACM International Conference on Information and Knowledge …, 2021 | 89 | 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 The Web Conference 2022 (WWW 2022), 2022 | 57 | 2022 |
| Fairness in Recommendation: A Survey Y Li, H Chen, S Xu, Y Ge, J Tan, S Liu, Y Zhang arXiv preprint arXiv:2205.13619, 2022 | 44 | 2022 |
| Explainable fairness in recommendation Y Ge, J Tan, Y Zhu, Y Xia, J Luo, S Liu, Z Fu, S Geng, Z Li, Y Zhang Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 42 | 2022 |
| Path Language Modeling over Knowledge Graphsfor Explainable Recommendation S Geng, Z Fu, J Tan, Y Ge, G De Melo, Y Zhang Proceedings of the ACM Web Conference 2022, 946-955, 2022 | 41 | 2022 |
| OpenAGI: When LLM Meets Domain Experts Y Ge, W Hua, J Ji, J Tan, S Xu, Y Zhang arXiv preprint arXiv:2304.04370, 2023 | 31 | 2023 |
| A survey on trustworthy recommender systems Y Ge, S Liu, Z Fu, J Tan, Z Li, S Xu, Y Li, Y Xian, Y Zhang arXiv preprint arXiv:2207.12515, 2022 | 30 | 2022 |
| Deconfounded causal collaborative filtering S Xu, J Tan, S Heinecke, VJ Li, Y Zhang ACM Transactions on Recommender Systems, 2021 | 23 | 2021 |
| Belief-space planning using learned models with application to underactuated hands A Kimmel, A Sintov, J Tan, B Wen, A Boularias, KE Bekris The International Symposium of Robotics Research, 642-659, 2019 | 14 | 2019 |
| Causal factorization machine for robust recommendation Y Li, H Chen, J Tan, Y Zhang Proceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries, 1-9, 2022 | 13 | 2022 |
| Dynamic Causal Collaborative Filtering S Xu, J Tan, Z Fu, J Ji, S Heinecke, Y Zhang Proceedings of the 31st ACM International Conference on Information …, 2022 | 12 | 2022 |
| VIP5: Towards Multimodal Foundation Models for Recommendation S Geng, J Tan, S Liu, Z Fu, Y Zhang arXiv preprint arXiv:2305.14302, 2023 | 11 | 2023 |
| 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 | 11 | 2021 |
| Fairness in Recommendation: Foundations, Methods, and Applications Y Li, H Chen, S Xu, Y Ge, J Tan, S Liu, Y Zhang ACM Transactions on Intelligent Systems and Technology 14 (5), 1-48, 2023 | 7 | 2023 |
| Counterfactual Collaborative Reasoning J Ji, Z Li, S Xu, M Xiong, J Tan, Y Ge, H Wang, Y Zhang Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 7 | 2023 |
| Causal Inference for Recommendation: Foundations, Methods and Applications S Xu, J Ji, Y Li, Y Ge, J Tan, Y Zhang arXiv preprint arXiv:2301.04016, 2023 | 6 | 2023 |
| GenRec: Large Language Model for Generative Recommendation J Ji, Z Li, S Xu, W Hua, Y Ge, J Tan, Y Zhang arXiv e-prints, arXiv: 2307.00457, 2023 | 5 | 2023 |
| ExplainableFold: Understanding AlphaFold Prediction with Explainable AI J Tan, Y Zhang 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), 2023 | 2 | 2023 |
| A Self-supervised Learning System for Object Detection in Videos Using Random Walks on Graphs J Tan, C Song, A Boularias 2021 IEEE International Conference on Robotics and Automation (ICRA 2021 …, 2021 | 2 | 2021 |
| User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations J Tan, Y Ge, Y Zhu, Y Xia, J Luo, J Ji, Y Zhang 26th European Conference on Artificial Intelligence (ECAI 2023), 2023 | 1 | 2023 |
Yongfeng ZhangRutgers University, Computer ScienceVerified email at rutgers.edu
