Yingqiang Ge
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
32
Venues
11
Active years
2019–2025
Best venue rank
A*
Where they publish
Papers
32 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | WWW | The 1st Workshop on Human-Centered Recommender Systems. | Kaike Zhang, Yunfan Wu, Yougang Lyu, Du Su, Yingqiang Ge, Shuchang Liu, Qi Cao, Zhaochun Ren, Fei Sun |
| 2024 | EACL | UP5: Unbiased Foundation Model for Fairness-aware Recommendation. | Wenyue Hua, Yingqiang Ge, Shuyuan Xu, Jianchao Ji, Zelong Li, Yongfeng Zhang |
| 2024 | ECIR | GenRec: Large Language Model for Generative Recommendation. | Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, Yongfeng Zhang |
| 2024 | SIGIR | IDGenRec: LLM-RecSys Alignment with Textual ID Learning. | Juntao Tan, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Zelong Li, Yongfeng Zhang |
| 2023 | CIKM | Logistics Audience Expansion via Temporal Knowledge Graph. | Hua Yan, Yingqiang Ge, Haotian Wang, Desheng Zhang, Yu Yang |
| 2023 | ECAI | User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. | Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang |
| 2023 | ICTIR | Causal Collaborative Filtering. | Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang |
| 2023 | WWW | Fairness-aware Differentially Private Collaborative Filtering. | Zhenhuan Yang, Yingqiang Ge, Congzhe Su, Dingxian Wang, Xiaoting Zhao, Yiming Ying |
| 2023 | WSDM | Counterfactual Collaborative Reasoning. | Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang |
| 2022 | ACL | Improving Personalized Explanation Generation through Visualization. | Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo, Yongfeng Zhang |
| 2022 | RecSys | Fairness-aware Federated Matrix Factorization. | Shuchang Liu, Yingqiang Ge, Shuyuan Xu, Yongfeng Zhang, Amlie Marian |
| 2022 | RecSys | Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). | Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang |
| 2022 | WWW | Path Language Modeling over Knowledge Graphsfor Explainable Recommendation. | Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang |
| 2022 | WWW | Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. | Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang |
| 2022 | SIGIR | Explainable Fairness in Recommendation. | Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang |
| 2022 | SIGIR | AutoLossGen: Automatic Loss Function Generation for Recommender Systems. | Zelong Li, Jianchao Ji, Yingqiang Ge, Yongfeng Zhang |
| 2022 | WSDM | Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning. | Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu, Chu-Cheng Hsieh, Yongfeng Zhang |
| 2021 | CIKM | CIKM 2021 Tutorial on Fairness of Machine Learning in Recommender Systems. | Yunqi Li, Yingqiang Ge, Yongfeng Zhang |
| 2021 | CIKM | Counterfactual Explainable Recommendation. | Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang |
| 2021 | WWW | User-oriented Fairness in Recommendation. | Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang |
| 2021 | WWW | Efficient Non-Sampling Knowledge Graph Embedding. | Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen, Yongfeng Zhang |
| 2021 | WWW | Variation Control and Evaluation for Generative Slate Recommendations. | Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang |
| 2021 | SIGIR | Towards Personalized Fairness based on Causal Notion. | Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang |
| 2021 | SIGIR | Tutorial on Fairness of Machine Learning in Recommender Systems. | Yunqi Li, Yingqiang Ge, Yongfeng Zhang |
| 2021 | SIGIR | Learning Causal Explanations for Recommendation. | Shuyuan Xu, Yunqi Li, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Xu Chen, Yongfeng Zhang |
| 2021 | WSDM | Towards Long-term Fairness in Recommendation. | Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang |
| 2020 | AAAI | ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs. | Zuohui Fu, Yikun Xian, Shijie Geng, Yingqiang Ge, Yuting Wang, Xin Dong, Guang Wang, Gerard de Melo |
| 2020 | CIKM | CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. | Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang |
| 2020 | SIGIR | Fairness-Aware Explainable Recommendation over Knowledge Graphs. | Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo |
| 2020 | SIGIR | Learning Personalized Risk Preferences for Recommendation. | Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, Yongfeng Zhang |
| 2020 | SIGIR | Understanding Echo Chambers in E-commerce Recommender Systems. | Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang |
| 2019 | WWW | Maximizing Marginal Utility per Dollar for Economic Recommendation. | Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Shijie Geng, Zuohui Fu, Yongfeng Zhang |