Maximizing Marginal Utility per Dollar for Economic Recommendation. - Yingqiang Ge; Shuyuan Xu; Shuchang Liu 001; Shijie Geng; Zuohui Fu; Yongfeng Zhang (WWW, 2019)

sharedCharging: Data-Driven Shared Charging for Large-Scale Heterogeneous Electric Vehicle Fleets. - Guang Wang 001; Wenzhong Li; Jun Zhang 014; Yingqiang Ge; Zuohui Fu; Fan Zhang 019; Yang Wang 015; Desheng Zhang (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019)

ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs. - Zuohui Fu; Yikun Xian; Shijie Geng; Yingqiang Ge; Yuting Wang; Xin Dong 010; Guang Wang 001; Gerard de Melo (AAAI, 2020)

CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. - Yikun Xian; Zuohui Fu; Handong Zhao; Yingqiang Ge; Xu Chen 017; Qiaoying Huang; Shijie Geng; Zhou Qin 001; Gerard de Melo; S. Muthukrishnan 001; Yongfeng Zhang (CIKM, 2020)

Fairness-Aware Explainable Recommendation over Knowledge Graphs. - Zuohui Fu; Yikun Xian; Ruoyuan Gao; Jieyu Zhao 004; Qiaoying Huang; Yingqiang Ge; Shuyuan Xu; Shijie Geng; Chirag Shah 001; Yongfeng Zhang; Gerard de Melo (SIGIR, 2020)

Learning Personalized Risk Preferences for Recommendation. - Yingqiang Ge; Shuyuan Xu; Shuchang Liu 001; Zuohui Fu; Fei Sun 001; Yongfeng Zhang (SIGIR, 2020)

Understanding Echo Chambers in E-commerce Recommender Systems. - Yingqiang Ge; Shuya Zhao; Honglu Zhou; Changhua Pei; Fei Sun 001; Wenwu Ou; Yongfeng Zhang (SIGIR, 2020)

CIKM 2021 Tutorial on Fairness of Machine Learning in Recommender Systems. - Yunqi Li 003; Yingqiang Ge; Yongfeng Zhang (CIKM, 2021)

Counterfactual Explainable Recommendation. - Juntao Tan; Shuyuan Xu; Yingqiang Ge; Yunqi Li 003; Xu Chen 017; Yongfeng Zhang (CIKM, 2021)

Towards Personalized Fairness based on Causal Notion. - Yunqi Li 003; Hanxiong Chen; Shuyuan Xu; Yingqiang Ge; Yongfeng Zhang (SIGIR, 2021)

Tutorial on Fairness of Machine Learning in Recommender Systems. - Yunqi Li 003; Yingqiang Ge; Yongfeng Zhang (SIGIR, 2021)

Towards Long-term Fairness in Recommendation. - Yingqiang Ge; Shuchang Liu 001; Ruoyuan Gao; Yikun Xian; Yunqi Li 003; Xiangyu Zhao 001; Changhua Pei; Fei Sun 001; Junfeng Ge; Wenwu Ou; Yongfeng Zhang (WSDM, 2021)

User-oriented Fairness in Recommendation. - Yunqi Li 003; Hanxiong Chen; Zuohui Fu; Yingqiang Ge; Yongfeng Zhang (WWW, 2021)

Efficient Non-Sampling Knowledge Graph Embedding. - Zelong Li; Jianchao Ji; Zuohui Fu; Yingqiang Ge; Shuyuan Xu; Chong Chen 001; Yongfeng Zhang (WWW, 2021)

Variation Control and Evaluation for Generative Slate Recommendations. - Shuchang Liu 001; Fei Sun 001; Yingqiang Ge; Changhua Pei; Yongfeng Zhang (WWW, 2021)

Variation Control and Evaluation for Generative SlateRecommendations. - Shuchang Liu 001; Fei Sun 001; Yingqiang Ge; Changhua Pei; Yongfeng Zhang (CoRR, 2021)

Counterfactual Evaluation for Explainable AI. - Yingqiang Ge; Shuchang Liu 001; Zelong Li; Shuyuan Xu; Shijie Geng; Yunqi Li 003; Juntao Tan; Fei Sun 001; Yongfeng Zhang (CoRR, 2021)

Improving Personalized Explanation Generation through Visualization. - Shijie Geng; Zuohui Fu; Yingqiang Ge; Lei Li 042; Gerard de Melo; Yongfeng Zhang (ACL (1), 2022)

Fairness-aware Federated Matrix Factorization. - Shuchang Liu 001; Yingqiang Ge; Shuyuan Xu; Yongfeng Zhang; Amélie Marian (RecSys, 2022)

Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). - Shijie Geng; Shuchang Liu 001; Zuohui Fu; Yingqiang Ge; Yongfeng Zhang (RecSys, 2022)

Explainable Fairness in Recommendation. - Yingqiang Ge; Juntao Tan; Yan Zhu; Yinglong Xia; Jiebo Luo 001; Shuchang Liu 001; Zuohui Fu; Shijie Geng; Zelong Li; Yongfeng Zhang (SIGIR, 2022)

AutoLossGen: Automatic Loss Function Generation for Recommender Systems. - Zelong Li; Jianchao Ji; Yingqiang Ge; Yongfeng Zhang (SIGIR, 2022)

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 (WSDM, 2022)

Path Language Modeling over Knowledge Graphsfor Explainable Recommendation. - Shijie Geng; Zuohui Fu; Juntao Tan; Yingqiang Ge; Gerard de Melo; Yongfeng Zhang (WWW, 2022)

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 003; Yongfeng Zhang (WWW, 2022)

Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning. - Yingqiang Ge; Xiaoting Zhao; Lucia Yu; Saurabh Paul; Diane Hu; Chu-Cheng Hsieh; Yongfeng Zhang (CoRR, 2022)

Fairness in Recommendation: A Survey. - Yunqi Li 003; Hanxiong Chen; Shuyuan Xu; Yingqiang Ge; Juntao Tan; Shuchang Liu 001; Yongfeng Zhang (CoRR, 2022)

A Survey on Trustworthy Recommender Systems. - Yingqiang Ge; Shuchang Liu 001; Zuohui Fu; Juntao Tan; Zelong Li; Shuyuan Xu; Yunqi Li 003; Yikun Xian; Yongfeng Zhang (CoRR, 2022)

FAIR: Fairness-aware information retrieval evaluation. - Ruoyuan Gao; Yingqiang Ge; Chirag Shah 001 (J. Assoc. Inf. Sci. Technol., 2022)

Logistics Audience Expansion via Temporal Knowledge Graph. - Hua Yan; Yingqiang Ge; Haotian Wang 008; Desheng Zhang; Yu Yang 010 (CIKM, 2023)

User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations. - Juntao Tan; Yingqiang Ge; Yan Zhu; Yinglong Xia; Jiebo Luo 001; Jianchao Ji; Yongfeng Zhang (ECAI, 2023)

Causal Collaborative Filtering. - Shuyuan Xu; Yingqiang Ge; Yunqi Li 003; Zuohui Fu; Xu Chen 017; Yongfeng Zhang (ICTIR, 2023)

OpenAGI: When LLM Meets Domain Experts. - Yingqiang Ge; Wenyue Hua; Kai Mei; Jianchao Ji; Juntao Tan; Shuyuan Xu; Zelong Li; Yongfeng Zhang (NeurIPS, 2023)

How to Index Item IDs for Recommendation Foundation Models. - Wenyue Hua; Shuyuan Xu; Yingqiang Ge; Yongfeng Zhang (SIGIR-AP, 2023)

Counterfactual Collaborative Reasoning. - Jianchao Ji; Zelong Li; Shuyuan Xu; Max Xiong; Juntao Tan; Yingqiang Ge; Hao Wang 014; Yongfeng Zhang (WSDM, 2023)

Fairness-aware Differentially Private Collaborative Filtering. - Zhenhuan Yang; Yingqiang Ge; Congzhe Su; Dingxian Wang; Xiaoting Zhao; Yiming Ying (WWW (Companion Volume), 2023)

Automated Data Denoising for Recommendation. - Yingqiang Ge; Mostafa Rahmani; Athirai A. Irissappane; Jose Sepulveda; James Caverlee; Fei Wang 065 (CoRR, 2023)

UP5: Unbiased Foundation Model for Fairness-aware Recommendation. - Wenyue Hua; Yingqiang Ge; Shuyuan Xu; Jianchao Ji; Yongfeng Zhang (CoRR, 2023)

War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars. - Wenyue Hua; Lizhou Fan; Lingyao Li; Kai Mei; Jianchao Ji; Yingqiang Ge; Libby Hemphill; Yongfeng Zhang (CoRR, 2023)

LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem. - Yingqiang Ge; Yujie Ren; Wenyue Hua; Shuyuan Xu; Juntao Tan; Yongfeng Zhang (CoRR, 2023)

Efficient Non-Sampling Graph Neural Networks. - Jianchao Ji; Zelong Li; Shuyuan Xu; Yingqiang Ge; Juntao Tan; Yongfeng Zhang (Inf., 2023)

Fairness in Recommendation: Foundations, Methods, and Applications. - Yunqi Li 003; Hanxiong Chen; Shuyuan Xu; Yingqiang Ge; Juntao Tan; Shuchang Liu 006; Yongfeng Zhang (ACM Trans. Intell. Syst. Technol., 2023)

UP5: Unbiased Foundation Model for Fairness-aware Recommendation. - Wenyue Hua; Yingqiang Ge; Shuyuan Xu; Jianchao Ji; Zelong Li; Yongfeng Zhang (EACL (1), 2024)

GenRec: Large Language Model for Generative Recommendation. - Jianchao Ji; Zelong Li; Shuyuan Xu; Wenyue Hua; Yingqiang Ge; Juntao Tan; Yongfeng Zhang (ECIR (3), 2024)

IDGenRec: LLM-RecSys Alignment with Textual ID Learning. - Juntao Tan; Shuyuan Xu; Wenyue Hua; Yingqiang Ge; Zelong Li; Yongfeng Zhang (SIGIR, 2024)

PAP-REC: Personalized Automatic Prompt for Recommendation Language Model. - Zelong Li; Jianchao Ji; Yingqiang Ge; Wenyue Hua; Yongfeng Zhang (CoRR, 2024)

AIOS: LLM Agent Operating System. - Kai Mei; Zelong Li; Shuyuan Xu; Ruosong Ye; Yingqiang Ge; Yongfeng Zhang (CoRR, 2024)

Towards LLM-RecSys Alignment with Textual ID Learning. - Juntao Tan; Shuyuan Xu; Wenyue Hua; Yingqiang Ge; Zelong Li; Yongfeng Zhang (CoRR, 2024)

The 1st Workshop on Human-Centered Recommender Systems. - Kaike Zhang; Yunfan Wu; Yougang Lyu; Du Su; Yingqiang Ge; Shuchang Liu 001; Qi Cao; Zhaochun Ren; Fei Sun 001 (WWW (Companion Volume), 2025)

Causal Inference for Recommendation: Foundations, Methods, and Applications. - Shuyuan Xu; Jianchao Ji; Yunqi Li 003; Yingqiang Ge; Juntao Tan; Yongfeng Zhang (ACM Trans. Intell. Syst. Technol., 2025)

A Survey on Trustworthy Recommender Systems. - Yingqiang Ge; Shuchang Liu 006; Zuohui Fu; Juntao Tan; Zelong Li; Shuyuan Xu; Yunqi Li 003; Yikun Xian; Yongfeng Zhang (Trans. Recomm. Syst., 2025)