Publications

Conference and Journal Publications

    2024

  • AIOS: LLM Agent Operating System
    Kai Mei, Zelong Li, Shuyuan Xu, Ruosong Ye, Yingqiang Ge, Yongfeng Zhang. [PDF]
  • Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents
    Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang. [PDF]
  • 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. [PDF]
  • TrustAgent: Towards Safe and Trustworthy LLM-based Agents through Agent Constitution
    Wenyue Hua, Xianjun Yang, Zelong Li, Cheng Wei, Yongfeng Zhang. [PDF]
  • 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. [PDF]
  • NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes
    Lizhou Fan, Wenyue Hua, Lingyao Li, Haoyang Ling, Yongfeng Zhang. [PDF]
  • NPHardEval4V: A Dynamic Reasoning Benchmark of Multimodal Large Language Models
    Lizhou Fan, Wenyue Hua, Xiang Li, Kaijie Zhu, Mingyu Jin, Lingyao Li, Haoyang Ling, Jinkui Chi, Jindong Wang, Xin Ma, Yongfeng Zhang. [PDF]
  • AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models
    Dong shu, Mingyu Jin, Suiyuan Zhu, Beichen Wang, Zihao Zhou, Chong Zhang, Yongfeng Zhang. [PDF]
  • Health-LLM: Personalized Retrieval-Augmented Disease Prediction Model
    Mingyu Jin, Qinkai Yu, Dong Shu, Chong Zhang, Suiyuan Zhu, Mengnan Du, Yanda Meng, Yongfeng Zhang. [PDF]
  • Towards LLM-RecSys Alignment based on Textual ID Learning
    Juntao Tan, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Zelong Li and Yongfeng Zhang. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), July 14 - 18, 2024, Washington D.C., USA. [PDF]
  • OpenP5: An Open-Source Platform for Developing, Training, and Evaluating LLM-based Recommender Systems
    Shuyuan Xu, Wenyue Hua and Yongfeng Zhang. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2024), July 14 - 18, 2024, Washington D.C., USA. [PDF]
  • Pre-trained Language Models for Entity Blocking: A Reproducibility Study
    Runhui Wang and Yongfeng Zhang. In Proceedings of the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024), June 16 - 21, 2024, Mexico City, Mexico. [PDF]
  • Language is All a Graph Needs
    Ruosong Ye, Caiqi Zhang, Runhui Wang, Shuyuan Xu and Yongfeng Zhang. In the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024), March 17 - 22, 2024, St. Julians, Malta. [PDF]
  • UP5: Unbiased Foundation Model for Fairness-aware Recommendation
    Wenyue Hua, Yingqiang Ge, Shuyuan Xu, Jianchao Ji, Yongfeng Zhang. In the 18th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024), March 17 - 22, 2024, St. Julians, Malta. [PDF]
  • A Survey on Trustworthy Recommender Systems
    Yingqiang Ge, Shuchang Liu, Zuohui Fu, Juntao Tan, Zelong Li, Shuyuan Xu, Yunqi Li, Yikun Xian and Yongfeng Zhang. In ACM Transactions on Recommender Systems (TORS). [PDF]
  • GenRec: Large Language Model for Generative Recommendation
    Jianchao Ji, Zelong Li, Shuyuan Xu, Wenyue Hua, Yingqiang Ge, Juntao Tan, Yongfeng Zhang. In Proceedings of the 46th European Conference on Information Retrieval (ECIR 2024), March 24 - 28, 2024, Glasgow, Scotland. [PDF]
  • Prompt-based Generative News Recommendation (PGNR): Accuracy and Controllability
    Xinyi Li, Yongfeng Zhang, Edward C. Malthouse. In Proceedings of the 46th European Conference on Information Retrieval (ECIR 2024), March 24 - 28, 2024, Glasgow, Scotland. [PDF]
  • Large Language Models for Generative Recommendation: A Survey and Visionary Discussions
    Lei Li, Yongfeng Zhang, Dugang Liu, Li Chen. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (COLING 2024), May 20 - 25, 2024, Turin, Italy. [PDF]
  • Neural Locality Sensitive Hashing for Blocking in Entity Resolution
    Runhui Wang, Luyang Kong, Yefan Tao, Andrew Borthwick, Davor Golac, Henrik Johnson, Shadie Hijazi, Dong Deng, Yongfeng Zhang. In Proceedings of the SIAM International Conference on Data Mining (SDM 2024), April 18 - 20, 2024, Houston, TX, US. [PDF]
  • Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training
    Juntao Tan, Shelby Heinecke, Zhiwei Liu, Yongjun Chen, Yongfeng Zhang, Huan Wang. In Proceedings of the SIAM International Conference on Data Mining (SDM 2024), April 18 - 20, 2024, Houston, TX, US. [PDF]

  • 2023

  • OpenAGI: When LLM Meets Domain Experts
    Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji, Juntao Tan, Shuyuan Xu, Zelong Li and Yongfeng Zhang. In Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), December 10 - December 16, New Orleans, Louisiana, US. [PDF]
  • How to Index Item IDs for Recommendation Foundation Models
    Wenyue Hua, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang. In Proceedings of 1st International ACM SIGIR Conference on Information Retrieval in the Asia Pacific (SIGIR-AP 2023), November 26 - 29, 2023, Beijing, China. [PDF]
  • VIP5: Towards Multimodal Foundation Models for Recommendation
    Shijie Geng, Juntao Tan, Shuchang Liu, Zuohui Fu, Yongfeng Zhang. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), December 6 - December 10, 2023, Singapore. [PDF]
  • Prompt Distillation for Efficient LLM-based Recommendation
    Lei Li, Yongfeng Zhang and Li Chen. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023), October 21 - 25, 2023, Birmingham, UK. [PDF]
  • Counterfactual Collaborative Reasoning
    Jianchao Ji, Zelong Li, Shuyuan Xu, Max Xiong, Juntao Tan, Yingqiang Ge, Hao Wang, Yongfeng Zhang. In Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2023), February 27 - March 3, 2023, Singapore. [PDF]
  • Causal Collaborative Filtering
    Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang. In Proceedings of The 9th ACM SIGIR / The 13th International Conference on the Theory of Information Retrieval (ICTIR 2023), July 23 - 27, 2023, Taipei, Taiwan. [PDF]
  • Deconfounded Causal Collaborative Filtering
    Shuyuan Xu, Juntao Tan, Shelby Heinecke, Jia Li, Yongfeng Zhang. In ACM Transactions on Recommender Systems (TORS). [PDF]
  • Causal Inference for Recommendation: Foundations, Methods and Applications
    Shuyuan Xu, Jianchao Ji, Yunqi Li, Yingqiang Ge, Juntao Tan, Yongfeng Zhang. arXiv:2301.04016. [PDF]
  • Fairness in Recommendation: Foundations, Methods and Applications
    Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Juntao Tan, Shuchang Liu and Yongfeng Zhang. In ACM Transactions on Intelligent Systems and Technology (TIST). [PDF]
  • ExplainableFold: Understanding AlphaFold Prediction with Explainable AI
    Juntao Tan and Yongfeng Zhang. In Proceedings of the 29th SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023), August 6 - 10, 2023, Long Beach, California, United States. [PDF]
  • User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations
    Juntao Tan, Yingqiang Ge, Yan Zhu, Yinglong Xia, Jiebo Luo, Jianchao Ji, Yongfeng Zhang. In Proceedings of the 26th European Conference on Artificial Intelligence (ECAI 2023), September 30 - October 5, 2023, Krakow, Poland. [PDF]
  • HiCLIP: Contrastive Language-Image Pretraining with Hierarchy-aware Attention
    Shijie Geng, Jianbo Yuan, Yu Tian, Yuxiao Chen, Yongfeng Zhang. In Proceedings of the Eleventh International Conference on Learning Representations (ICLR 2023), May 1 - 5, 2023, Kigali, Rwanda. [PDF]
  • The Dark Side of Explanations: Poisoning Recommender Systems with Counterfactual Examples
    Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, Gabriele Tolomei. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2023), July 23 - 27, 2023, Taipei, Taiwan. [PDF]
  • Exploration and Regularization of the Latent Action Space in Recommendation
    Shuchang Liu, Qingpeng Cai, Bowen Sun, Yuhao Wang, Dong Zheng, Peng Jiang, Kun Gai, Ji Jiang, Xiangyu Zhao and Yongfeng Zhang. In Proceedings of the Web Conference 2023 (WWW 2023), April 30 - May 4, 2023, Texas, Austin, US. [PDF]
  • Discover, Explain, Improve: An Automatic Slice Detection Benchmark for Natural Language Processing
    Wenyue Hua, Lifeng Jin, Linfeng Song, Haitao Mi, Yongfeng Zhang, Dong Yu. In Transactions of the Association for Computational Linguistics (TACL). [PDF]
  • Personalized Prompt Learning for Explainable Recommendation
    Lei Li, Yongfeng Zhang, Li Chen. In ACM Transactions on Information Systems (TOIS). [PDF]
  • A Reusable Model-agnostic Framework for Faithfully Explainable Recommendation and System Scrutability
    Zhichao Xu, Hansi Zeng, Juntao Tan, Zuohui Fu, Yongfeng Zhang, Qingyao Ai. In ACM Transactions on Information Systems (TOIS). [PDF]
  • Sparks of Artificial General Recommender (AGR): Early Experiments with ChatGPT
    Guo Lin, Yongfeng Zhang. Algorithms. 2023. Special Issue on New Trends in Algorithms for Intelligent Recommendation Systems. [PDF]
  • Clip-adapter: Better Vision-Language Models with Feature Adapters
    Peng Gao, Shijie Geng, Renrui Zhang, Teli Ma, Rongyao Fang, Yongfeng Zhang, Hongsheng Li, Yu Qiao. In International Journal of Computer Vision (IJCV). [PDF]
  • On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance
    Lei Li, Yongfeng Zhang, Li Chen. In ACM Transactions on Intelligent Systems and Technology (TIST). [PDF]

  • 2022

  • Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5)
    Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge and Yongfeng Zhang. In Proceedings of the 16th ACM Conference on Recommender Systems (RecSys 2022), September 18 - 23, 2022, Seattle, WA, USA. [PDF][Slides]
  • Fairness-aware Federated Matrix Factorization
    Shuchang Liu, Yingqiang Ge, Shuyuan Xu, Yongfeng Zhang and Amelie Marian. In Proceedings of the 16th ACM Conference on Recommender Systems (RecSys 2022), September 18 - 23, 2022, Seattle, WA, USA. [PDF][Slides]
  • Dynamic Causal Collaborative Filtering
    Shuyuan Xu, Juntao Tan, Zuohui Fu, Jianchao Ji, Shelby Heinecke and Yongfeng Zhang. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), October 17 - 21, 2022, Hybrid Conference, Hosted in Atlanta, Georgia, USA. [PDF]
  • Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)
    Hanxiong Chen, Yunqi Li, He Zhu and Yongfeng Zhang. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM 2022), October 17 - 21, 2022, Hybrid Conference, Hosted in Atlanta, Georgia, USA. [PDF]
  • AutoLossGen: Automatic Loss Function Generation for Recommender Systems
    Zelong Li, Jianchao Ji, Yingqiang Ge and Yongfeng Zhang. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), July 11 - 15, 2022, Madrid, Spain. [PDF]
  • Explainable Fairness in Recommendation
    Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li and Yongfeng Zhang. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022), July 11 - 15, 2022, Madrid, Spain. [PDF]
  • From Kepler to Newton: Explainable AI for Science Discovery
    Zelong Li, Jianchao Ji, Yongfeng Zhang. ICML-AI4Science 2022. [PDF][Video and Slides]
  • 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 and Yongfeng Zhang. In Proceedings of the Web Conference 2022 (WWW 2022), April 25 - 29, 2022, Lyon, France. [PDF]
  • Path Language Modeling over Knowledge Graphs for Explainable Recommendation
    Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo and Yongfeng Zhang. In Proceedings of the Web Conference 2022 (WWW 2022), April 25 - 29, 2022, Lyon, France. [PDF]
  • ExpScore: Learning Metrics for Recommendation Explanation
    Bingbing Wen, Yunhe Feng, Yongfeng Zhang and Chirag Shah. In Proceedings of the Web Conference 2022 (WWW 2022), April 25 - 29, 2022, Lyon, France. [PDF]
  • Improving Personalized Explanation Generation through Visualization
    Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo and Yongfeng Zhang. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), May 22 - 27, 2022, Dublin, Ireland. [PDF]
  • System 1 + System 2 = Better World: Neural-Symbolic Chain of Logic Reasoning
    Wenyue Hua and Yongfeng Zhang. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 7 – 11, 2022, Abu Dhabi. [PDF]
  • Data-Efficient Concept Extraction from Pre-trained Language Models for Commonsense Explanation Generation
    Yanbo Fang and Yongfeng Zhang. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), December 7 – 11, 2022, Abu Dhabi. [PDF]
  • Assessing Combinational Generalization of Language Models in Biased Scenarios
    Yanbo Fang, Zuohui Fu, Xin Dong, Yongfeng Zhang and Gerard de Melo. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL 2022), November 20 - 23, 2022, Online. [PDF]
  • Causal Factorization Machine for Robust Recommendation
    Yunqi Li, Hanxiong Chen, Juntao Tan and Yongfeng Zhang. In Proceedings of ACM/IEEE Joint Conference on Digital Libraries (JCDL 2022), June 20 - 24, 2022, Cologne, Germany and Online. [PDF]
  • Graph Collaborative Reasoning
    Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu and Yongfeng Zhang. In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 21 - 25, 2022, Phoenix, Arizona. [PDF]
  • Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning
    Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu and Yongfeng Zhang. In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 21 - 25, 2022, Phoenix, Arizona. [PDF]
  • RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems
    Zohreh Ovaisi, Shelby Heinecke, Jia Li, Yongfeng Zhang, Elena Zheleva and Caiming Xiong. In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022), February 21 - 25, 2022, Phoenix, Arizona. [PDF]
  • Data Augmented Sequential Recommendation based on Counterfactual Thinking
    Xu Chen, Zhenlei Wang, Hongteng Xu, Jingsen Zhang, Yongfeng Zhang, Xin Zhao, Ji-Rong Wen. In IEEE Transactions on Knowledge and Data Engineering (TKDE). [PDF]
  • Causal Structure Learning with Recommendation System
    Shuyuan Xu, Da Xu, Evren Korpeoglu, Sushant Kumar, Stephen Guo, Kannan Achan, Yongfeng Zhang. arXiv:2210.10256. [PDF]
  • Measuring "Why" in Recommender Systems: a Comprehensive Survey on the Evaluation of Explainable Recommendation
    Xu Chen, Yongfeng Zhang, Ji-Rong Wen. arXiv:2202.06466. [PDF]
  • Improving Neural Topic Modeling via Sinkhorn Divergence
    Luyang Liu, Heyan Huang, Yang Gao and Yongfeng Zhang. Information Processing & Management (IP&M), Volume 59 Issue 3. [PDF]
  • Looking Further into the Future: Career Pathway Prediction
    Michiharu Yamashita, Yunqi Li, Thanh Tran, Yongfeng Zhang and Dongwon Lee. In Proceedings of the First International Workshop on Computational Jobs Marketplace co-located with WSDM 2022, February 25, 2022, Phoenix, Arizona. [PDF]
  • Neural Logic Analogy Learning
    Yujia Fan and Yongfeng Zhang. In Proceedings of the ICLR 2022 Workshop on PAIR2Struct: Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data, April 29, 2022, Virtual. [PDF]
  • GREASE: Generate Factual and Counterfactual Explanations for GNN-based Recommendations
    Ziheng Chen, Fabrizio Silvestri, Jia Wang, Yongfeng Zhang, Zhenhua Huang, and Gabriele Tolomei. In Proceedings of the KDD 2022 Workshop on End-End Customer Journey Optimization, August 15, 2022, Washington DC. [PDF]

  • 2021

  • Neural Collaborative Reasoning
    Hanxiong Chen, Shaoyun Shi, Yunqi Li and Yongfeng Zhang. In Proceedings of the Web Conference 2021 (WWW 2021), April 19 - 23, 2021, Ljubljana, Slovenia. [PDF]
  • User-oriented Fairness in Recommendation
    Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge and Yongfeng Zhang. In Proceedings of the Web Conference 2021 (WWW 2021), April 19 - 23, 2021, Ljubljana, Slovenia. [PDF]
  • Variation Control and Evaluation for Generative Slate Recommendations
    Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei and Yongfeng Zhang. In Proceedings of the Web Conference 2021 (WWW 2021), April 19 - 23, 2021, Ljubljana, Slovenia. [PDF]
  • Efficient Non-Sampling Knowledge Graph Embedding
    Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen and Yongfeng Zhang. In Proceedings of the Web Conference 2021 (WWW 2021), April 19 - 23, 2021, Ljubljana, Slovenia. [PDF]
  • Personalized Transformer for Explainable Recommendation
    Lei Li, Yongfeng Zhang and Li Chen. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL 2021), August 1 - 6, 2021, Bangkok, Thailand. [PDF]
  • Problem Learning: Towards the Free Will of Machines
    Yongfeng Zhang. arXiv:2109.00177. [PDF]
  • Counterfactual Explainable Recommendation
    Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen and Yongfeng Zhang. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 1 - 5, 2021, Gold Coast, Australia. [PDF]
  • Counterfactual Review-based Recommendation
    Kun Xiong, Wenwen Ye, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Binbin Hu, Zhiqiang Zhang and Jun Zhou. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 1 - 5, 2021, Gold Coast, Australia. [PDF]
  • Popcorn: Human-in-the-loop Popularity Debiasing in Conversational Recommender Systems
    Zuohui Fu, Yikun Xian, Shijie Geng, Gerard de Melo and Yongfeng Zhang. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 1 - 5, 2021, Gold Coast, Australia. [PDF]
  • EX3: Explainable Attribute-aware Item-set Recommendations
    Yikun Xian, Tong Zhao, Jin Li, Jim Chan, Andrey Kan, Jun Ma, Xin Luna Dong, Christos Faloutsos, George Karypis, Shan Muthukrishnan, Yongfeng Zhang. In Proceedings of the 15th ACM Recommender Systems Conference (RecSys 2021), September 27 - October 1, 2021, Amsterdam, Netherland. [PDF]
  • Counterfactual Evaluation for Explainable AI
    Yingqiang Ge, Shuchang Liu, Zelong Li, Shuyuan Xu, Shijie Geng, Yunqi Li, Juntao Tan, Fei Sun, Yongfeng Zhang. arXiv:2109.01962. [PDF]
  • Towards Personalized Fairness based on Causal Notion
    Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge and Yongfeng Zhang. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
  • FedCT: Federated Collaborative Transfer for Recommendation
    Shuchang Liu, Shuyuan Xu, Wenhui Yu, Zuohui Fu, Yongfeng Zhang and Amelie Marian. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
  • Counterfactual Data-Augmented Sequential Recommendation
    Zhenlei Wang, Jingsen Zhang, Hongteng Xu, Xu Chen, Yongfeng Zhang, Wayne Xin Zhao and Ji-Rong Wen. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
  • HOOPS: Human-in-the-Loop Graph Reasoning for Conversational Recommendation
    Zuohui Fu, Yikun Xian, Yaxin Zhu, Shuyuan Xu, Zelong Li, Gerard de Melo and Yongfeng Zhang. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
  • EXTRA: Explanation Ranking Datasets for Explainable Recommendation
    Lei Li, Yongfeng Zhang and Li Chen. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
  • 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, and Yongfeng Zhang. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021), March 8 - 12, 2021, Virtual Event, Israel. [PDF]
  • Faithfully Explainable Recommendation via Neural Logic Reasoning
    Yaxin Zhu, Yikun Xian, Zuohui Fu, Gerard de Melo and Yongfeng Zhang. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2021), June 6 - 11, 2021, Mexico City, Mexico. [PDF]
  • Dynamic Graph Representation Learning for Video Dialog via Multi-Modal Shuffled Transformers
    Shijie Geng, Peng Gao, Moitreya Chatterjee, Chiori Hori, Jonathan LeRoux, Yongfeng Zhang, Hongsheng Li, Anoop Cherian. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2 - 9, 2021, Virtual Event. [PDF]
  • Learning Causal Explanations for Recommendation
    Shuyuan Xu, Yunqi Li, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Xu Chen, Yongfeng Zhang. In Proceedings of the 1st International Workshop on Causality in Search and Recommendation, July 15, 2021, Virtual Event, Canada. [PDF]
  • Romebert: Robust Training of Multi-exit Bert
    Shijie Geng, Peng Gao, Zuohui Fu, Yongfeng Zhang. arXiv:2101.09755. [PDF]

  • 2020

  • Explainable Recommendation: A Survey and New Perspectives
    Yongfeng Zhang and Xu Chen. Foundations and Trends in Information Retrieval: Vol. 14, No. 1, pp 1-101. Now Publishers. [PDF]
  • Neural Logic Reasoning
    Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang and Yongfeng Zhang. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19 - 23, 2020, Virtual Event, Ireland. [PDF]
  • 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. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19 - 23, 2020, Virtual Event, Ireland. [PDF]
  • Generate Neural Template Explanations for Recommendation
    Lei Li, Yongfeng Zhang, Li Chen. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19 - 23, 2020, Virtual Event, Ireland. [PDF]
  • E-commerce Recommendation with Weighted Expected Utility
    Zhichao Xu, Yi Han, Yongfeng Zhang, Qingyao Ai. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM 2020), October 19 - 23, 2020, Virtual Event, Ireland. [PDF]
  • A Representation Learning Approach to Animal Biodiversity Conservation
    Meet Mukadam, Mandhara Jayaram and Yongfeng Zhang. In Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), December 8 - 13, 2020, Online, Barcelona. [PDF]
  • Learning Personalized Risk Preferences for Recommendation
    Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun and Yongfeng Zhang. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25 - 30, 2020, Virtual Event, China. [PDF]
  • 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 and Gerard de Melo. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25 - 30, 2020, Virtual Event, China. [PDF]
  • Understanding Echo Chambers in E-commerce Recommender Systems
    Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou and Yongfeng Zhang. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25 - 30, 2020, Virtual Event, China. [PDF]
  • Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation
    Shaoyun Shi, Weizhi Ma, Min Zhang, Yongfeng Zhang, Xinxing Yu, Houzhi Shan, Yiqun Liu and Shaoping Ma. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25 - 30, 2020, Virtual Event, China. [PDF]
  • HID: Hierarchical Multiscale Representation Learning for Information Diffusion
    Honglu Zhou, Shuyuan Xu, Zuohui Fu, Gerard de Melo, Yongfeng Zhang, Mubbasir Kapadia. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), July 11 - 17, 2020, Virtual Event, Japan. [PDF]
  • Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation
    Chong Chen, Min Zhang, Weizhi Ma, Yongfeng Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020), February 7 - 12, 2020, New York, USA. [PDF]
  • IART: Intent-aware Response Ranking with Transformers in Information-seeking Conversation Systems
    Liu Yang, Minghui Qiu, Chen Qu, Cen Chen, Jiafeng Guo, Yongfeng Zhang, W. Bruce Croft, Haiqing Chen. In Proceedings of the Web Conference 2020 (WWW 2020), April 20 - 24, 2020, Virtual Event, Taipei. [PDF]
  • Towards Controllable Explanation Generation for Recommender Systems via Neural Template
    Lei Li, Li Chen, Yongfeng Zhang. In Proceedings of the Web Conference 2020 (WWW 2020), April 20 - 24, 2020, Virtual Event, Taipei. [PDF]
  • Efficient Neural Matrix Factorization without Sampling for Recommendation
    Chong Chen, Min Zhang, Yongfeng Zhang, Yiqun Liu and Shaoping Ma. In ACM Transactions on Information Systems (TOIS). [PDF]
  • Neural Feature-aware Recommendation with Signed Hypergraph Convolutional Network
    Xu Chen, Kun Xiong, Yongfeng Zhang, Long Xia, Dawei Yin, Jimmy Xiangji Huang. In ACM Transactions on Information Systems (TOIS). [PDF]
  • FairCharge: A Data-Driven Fairness-Aware Charging Recommendation System for Large-Scale Electric Taxi Fleets
    Guang Wang, Yongfeng Zhang, Zhihan Fang, Shuai Wang, Fan Zhang, Desheng Zhang. In Proceedings of the ACM Conference on Interactive, Mobile, Wearable and Ubiquitous Technologies (UBICOMP 2020). [PDF]
  • Neural-Symbolic Reasoning over Knowledge Graph for Multi-Stage Explainable Recommendation
    Yikun Xian, Zuohui Fu, Qiaoying Huang, S. Muthukrishnan and Yongfeng Zhang. In Proceedings of the 2020 AAAI Workshop on Deep Learning on Graphs: Methodologies and Applications, February 7 - 12, 2020, New York, USA. [PDF]
  • Discrete Knowledge Graph Embedding based on Discrete Optimization
    Yunqi Li, Shuyuan Xu, Zuohui Fu, Shuchang Liu, Bo Liu, Xu Chen and Yongfeng Zhang. In Proceedings of the AAAI-20 Workshop on Knowledge Discovery from Unstructured Data in Financial Services, February 7 - 12, 2020, New York, USA. [PDF]

  • 2019

  • Reinforcement Knowledge Graph Reasoning for Explainable Recommendation
    Yikun Xian, Zuohui Fu, Shan Muthukrishnan, Gerard de Melo and Yongfeng Zhang. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • Unified Collaborative Filtering over Graph Embeddings
    Pengfei Wang, Hanxiong Chen, Yadong Zhu, Huawei Shen and Yongfeng Zhang. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • BERT with History Answer Embedding for Conversational Question Answering
    Chen Qu, Liu Yang, Minghui Qiu, W. Bruce Croft, Yongfeng Zhang and Mohit Iyyer. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network: Towards Visually Explainable Recommendation
    Xu Chen, Hanxiong Chen, Hongteng Xu, Yongfeng Zhang, Yixin Cao, Hongyuan Zha and Zheng Qin. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • Hierarchical Matching Network for Crime Classification
    Pengfei Wang, Yu Fan, Yongfeng Zhang, Shuzi Niu, Ze Yang and Jiafeng Guo. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation
    Xin Xin, Xiangnan He, Yongfeng Zhang, Yongdong Zhang and Joemon Jose. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
  • Maximizing Marginal Utility per Dollar for Economic Recommendation
    Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Shijie Geng, Zuohui Fu and Yongfeng Zhang. In Proceedings of the Web Conference 2019 (WWW 2019), May 13 - 17, 2019, San Francisco, USA. [PDF]
  • Value-aware Recommendation based on Reinforcement Profit Maximization
    Changhua Pei, Xinru Yang, Qing Cui, Xiao Lin, Fei Sun, Peng Jiang, Wenwu Ou and Yongfeng Zhang. In Proceedings of the Web Conference 2019 (WWW 2019), May 13 - 17, 2019, San Francisco, USA. [PDF][Code][Data]
  • Neural Variational Correlated Topic Modeling
    Luyang Liu, Heyan Huang, Yang Gao, Xiaochi Wei and Yongfeng Zhang. In Proceedings of the Web Conference 2019 (WWW 2019), May 13 - 17, 2019, San Francisco, USA. [PDF]
  • Dynamic Explainable Recommendation based on Neural Attentive Models
    Xu Chen, Yongfeng Zhang, Zheng Qin. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), January 27 – February 1, 2019, Hawaii, USA. [PDF][Code]
  • Conversational Product Search Based on Negative Feedback
    Keping Bi, Qingyao Ai, Yongfeng Zhang and W. Bruce Croft. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), November 3 - 7, 2019, Beijing, China. [PDF]
  • Attentive History Selection for Conversational Question Answering
    Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft and Mohit Iyyer. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), November 3 - 7, 2019, Beijing, China. [PDF]
  • Adaptive Feature Sampling for Recommendation with Missing Content Feature Values
    Shaoyun Shi, Min Zhang, Xinxing Yu, Yongfeng Zhang, Bin Hao, Yiqun Liu and Shaoping Ma. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM 2019), November 3 - 7, 2019, Beijing, China. [PDF]
  • A Pareto-Efficient Algorithm for Multiple Objective Optimization in E-Commerce Recommendation
    Xiao Lin, Hongjie Chen, Changhua Pei, Fei Sun, Xuanji Xiao, Hanxiao Sun, Yongfeng Zhang, Peng Jiang, Wenwu Ou. In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019), Sep 16-20, 2019, Copenhagen, Denmark. . [PDF]
  • Personalized Re-ranking for Recommendation
    Changhua Pei, Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Junfeng Ge, Wenwu Ou. In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019), September 16 - 20, 2019, Copenhagen, Denmark. [PDF]
  • Explainable Product Search with a Dynamic Relation Embedding Model
    Qingyao Ai, Yongfeng Zhang, Keping Bi, W. Bruce Croft. In ACM Transactions on Information Systems (TOIS). [PDF]
  • Attentive Aspect Modeling for Review-aware Recommendation
    Xinyu Guan, Zhiyong Cheng, Xiangnan He, Yongfeng Zhang, Zhibo Zhu, Qinke Peng, Tat-Seng Chua. In ACM Transactions on Information Systems (TOIS). [PDF]
  • User Intent Prediction in Information-seeking Conversations
    Chen Qu, Liu Yang, Bruce Croft, Yongfeng Zhang, Johanne R Trippas and Minghui Qiu. In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), March 10 – 14, 2019, Glasgow, Scotland, UK. [PDF][Code]
  • Answer Interaction in Non-factoid Question Answering Systems
    Chen Qu, Liu Yang, Bruce Croft, Falk Scholer and Yongfeng Zhang. In Proceedings of the 2019 ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR 2019), March 10 – 14, 2019, Glasgow, Scotland, UK. [PDF]

  • 2018

  • Towards Conversational Search and Recommendation: System Ask, User Respond
    Yongfeng Zhang, Xu Chen, Qingyao Ai, Liu Yang, and W. Bruce Croft. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM 2018), October 22 - 26, 2018, Turin, Italy. [PDF]
  • Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
    Qingyao Ai, Vahid Azizi, Xu Chen, Yongfeng Zhang. Algorithms. 2018, 11(9). Special Issue Collaborative Filtering and Recommender Systems. [PDF]
  • Adversarial Distillation for Efficient Recommendation with External Knowledge
    Xu Chen, Yongfeng Zhang, Hongteng Xu, Zheng Qin, Hongyuan Zha. In ACM Transactions on Information Systems (TOIS). [PDF]
  • Modeling Dynamic Pairwise Attention for Crime Classification over Legal Articles
    Pengfei Wang, Ze Yang, Shu Zi, Yongfeng Zhang, Lei Zhang and Shaozhang Niu. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 - 12, 2018, Ann Arbor, Michigan, USA. [PDF]
  • Response Ranking with Deep Matching Networks and External Knowledge in Information-seeking Conversation Systems
    Liu Yang, Minghui Qiu, Chen Qu, Jiafeng Guo, Yongfeng Zhang, Bruce Croft, Jun Huang, Haiqing Chen. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 - 12, 2018, Ann Arbor, Michigan, USA. [PDF]
  • Analyzing and Characterizing User Intent in Information-seeking Conversations
    Chen Qu, Liu Yang, Bruce Croft, Johanne R Trippas, Yongfeng Zhang and Minghui Qiu. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 - 12, 2018, Ann Arbor, Michigan, USA. [PDF]
  • Sequential Recommendation with User Memory Networks
    Xu Chen, Hongteng Xu, Yongfeng Zhang, Jiaxi Tang, Yixin Cao, Zheng Qin, and Hongyuan Zha. In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM 2018), February 5 - 9, 2018, Los Angeles, California, USA. [PDF]
  • Explainable Recommendation: A Survey and New Perspectives
    Yongfeng Zhang and Xu Chen. arXiv Preprint 2018. arXiv:1804.11192. [PDF]

  • 2017

  • Learning a Hierarchical Embedding Model for Personalized Product Search
    Qingyao Ai, Yongfeng Zhang, Keping Bi, Xu Chen, and W. Bruce Croft. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), August 7 - 11, 2017, Tokyo, Japan. [PDF][slides][code]
  • Personalized Key Frame Recommendation
    Xu Chen, Yongfeng Zhang, Qingyao Ai, Hongteng Xu, Junchi Yan, and Zheng Qin. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017), August 7 - 11, 2017, Tokyo, Japan. [PDF][slides][code]
  • Multi-Product Utility Maximization for Economic Recommendation
    Qi Zhao, Yongfeng Zhang, Yi Zhang, and Daniel Friedman. In Proceedings of the 10th International Conference on Web Search and Data Mining (WSDM 2017), February 6 - 10, 2017, Cambridge, UK. [PDF][slides][code]
  • Joint Representation Learning for Top-N Recommendation with Heterogenous Information Sources
    Yongfeng Zhang, Qingyao Ai, Xu Chen, and W. Bruce Croft. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM 2017), November 6 - 10, 2017, Singapore. [PDF][slides][code]
  • Learning and Transferring Social and Item Visibilities for Personalized Recommendation
    Xiao Lin, Min Zhang, Yongfeng Zhang, Yiqun Liu, and Shaoping Ma. In Proceedings of the 26th ACM International Conference on Information and Knowledge Management (CIKM 2017), November 6 - 10, 2017, Singapore. [PDF][slides]
  • Fairness-Aware Group Recommendation with Pareto Efficiency
    Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu, Yiqun Liu, Shaoping Ma. In Proceedings of the 11th ACM Conference on Recommender Systems (RecSys 2017), August 27 - 31, 2017, Como, Italy. [PDF]
  • A Collaborative Neural Model for Rating Prediction by Leveraging User Reviews and Product Images
    Wenwen Ye, Yongfeng Zhang, Wayne Xin Zhao, Xu Chen, Zheng Qin. In Proceedings of the 13th Asia Information Retrieval Societies Conference (AIRS 2017), November 22 - 24, 2017, Jeju Island, Korea. Best Paper Award. [PDF]
  • Probabilistic Local Matrix Factorization based on User Reviews
    Xu Chen, Yongfeng Zhang, Wayne Xin Zhao, Wenwen Ye, Zheng Qin. In Proceedings of the 13th Asia Information Retrieval Societies Conference (AIRS 2017), November 22 - 24, 2017, Jeju Island, Korea. [PDF]
  • Detecting Stress Based on Social Interactions in Social Networks
    Huijie Lin, Jia Jia, Jiezhong Qiu, Yongfeng Zhang, Guangyao Shen, Lexing Xie, Jie Tang, Ling Feng, and Tat-Seng Chua. In IEEE Transactions on Knowledge and Data Engineering (TKDE), Mar 2017. [PDF]
  • Neural Matching Models for Question Retrieval and Next Question Prediction in Conversation
    Liu Yang, Hamed Zamani, Yongfeng Zhang, Jiafeng Guo, and W. Bruce Croft. In Proceedings of the SIGIR 2017 Workshop on Neural Information Retrieval (NEUIR 2017), August 7 - 11, 2017, Tokyo, Japan. [PDF]
  • Boosting Moving Average Reversion Strategy for Online Portfolio Selection: A Meta-Learning Approach
    Xiao Lin, Min Zhang, Yongfeng Zhang, Yiqun Liu, and Shaoping Ma. In Proceedings of the 22nd International Conference on Database Systems for Advanced Applications (DASFAA 2017), March 27 - 30, 2017, Suzhou, China. [PDF][slides]
  • Disparity-Aware Group Formation for Recommendation
    Xiao Lin, Min Zhang, Yongfeng Zhang, Zhaoquan Gu. In Proceedings of the Sixteenth International Conference on Antonomous Agents and Multiagent Sytems (AAMAS 2017), May 8 - 12, 2017, Sao Paulo, Brazil. [PDF]
  • Explainable Recommendation: Theory and Applications
    Yongfeng Zhang. arXiv Preprint 2017. arXiv:1708.06409. [PDF]

  • 2016

  • Economic Recommendation with Surplus Maximization
    Yongfeng Zhang, Qi Zhao, Yi Zhang, Daniel Friedman, Min Zhang, Yiqun Liu, and Shaoping Ma. In Proceedings of the 25th International World Wide Web Conference (WWW 2016), April 11 - 15, 2016, Montreal, Canada. [PDF][slides][code]
  • Learning to Rank Features for Recommendation over Multiple Categories
    Xu Chen, Zheng Qin, Yongfeng Zhang, and Tao Xu. In Proceedings of the 39th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2016), July 17 - 21, 2016, Pisa, Italy. [PDF][slides]
  • HLBPR: A Hybrid Local Bayesian Personal Ranking Method
    Xu Chen, Pengfei Wang, Zheng Qin, and Yongfeng Zhang. In Proceedings of the 25th International World Wide Web Conference (WWW 2016) (poster), April 11 - 15, 2016, Montreal, Canada. [PDF][poster]

  • 2015

  • Daily-Aware Personalized Recommendation based on Feature-Level Time Series Analysis
    Yongfeng Zhang, Min Zhang, Yi Zhang, Guokun Lai, Yiqun Liu, Honghui Zhang, Shaoping Ma. In Proceedings of the 24th International World Wide Web Conference (WWW 2015), May 18 - 22, 2015, Florence, Italy. [PDF][slides]
  • Catch the Black Sheep: Unified Framework for Shilling Attack Detection based on Fraudulent Action Propagation
    Yongfeng Zhang, Yunzhi Tan, Min Zhang, Yiqun Liu, Chua Tat-Seng, and Shaoping Ma. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), July 25 - 31, 2015, Buenos Aires, Argentina. [PDF][slides]
  • Incorporating Phrase-level Sentiment Analysis on Textual Reviews for Personalized Recommendation
    Yongfeng Zhang. In Proceedings of the 8th International Conference on Web Search and Data Mining (WSDM 2015), Feb. 2 - 6, 2015, Shanghai, China. [PDF]
  • Task-based Recommendation on a Web-Scale
    Yongfeng Zhang, Min Zhang, Yiqun Liu, Chua Tat-Seng, Yi Zhang, Shaoping Ma. In Proceedings of the 2015 IEEE International Conference on Big Data (BigData 2015), Oct 29 - Nov 1, 2015, Santa Clara, CA, USA. [PDF]
  • Exploration of Semantic-aware Approach for Contextual Suggestion Using Knowledge from The Open Web
    Yuan Wang, Yongfeng Zhang, Yi Zhang, Xintong Zhang, Jie Liu, and Yalou Huang. In Proceedings of the 24th Text REtrieval Conference (TREC 2015), Nov. 17 - 20, 2015, Gaithersburg, Maryland, USA. [PDF]
  • SoF: Soft-Cluster Matrix Factorization for Probabilistic Clustering
    Han Zhao, Pascal Poupart, Yongfeng Zhang, and Martin Lysy. In Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI 2015), Jan. 25 - 29, 2015, Austin, Texas, USA. [PDF]
  • Boost Phrase-level Polarity Labelling with Review-level Sentiment Classification
    Yongfeng Zhang, Min Zhang, Yiqun Liu and Shaoping Ma. arXiv Preprint 2015. arXiv:1502.03322. [PDF]

  • 2014

  • Explicit Factor Models for Explainable Recommendation based on Phrase-level Sentiment Analysis
    Yongfeng Zhang, Guokun Lai, Min Zhang, Yi Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2014), July 6 - 11, 2014, Gold Coast, Australia. [PDF][slides][code]
  • Do Users Rate or Review? Boost Phrase-level Sentiment Labeling with Review-level Sentiment Classification
    Yongfeng Zhang, Haochen Zhang, Min Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 37th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2014) (short paper), July 6 - 11, 2014, Gold Coast, Australia. [PDF][poster]
  • Understanding the Sparsity: Augmented Matrix Factorization with Sampled Constraints on Unobservables
    Yongfeng Zhang, Min Zhang, Yi Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014), Nov. 3 - 7, 2014, Shanghai, China. [PDF][Supplementary]
  • Browser-Oriented Universal Cross-Site Recommendation and Explanation based on User Browsing Logs
    Yongfeng Zhang. In Proceedings of the 8th ACM Conference Series on Recommender Systems (RecSys 2014), Oct. 6 - 10, 2014, Foster City, Silicon Valley, USA. [PDF][slides]

  • 2013

  • Localized Matrix Factorization for Recommendation based on Matrix Block Diagonal Forms
    Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma and Shi Feng. In Proceedings of the 22nd International Conference on World Wide Web (WWW 2013), May 13 - 17, 2013, Rio de Janeiro, Brazil. [PDF][slides][code]
  • Improve Collaborative Filtering Through Bordered Block Diagonal Form Matrices
    Yongfeng Zhang, Min Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 36th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval (SIGIR 2013), July 28 - August 1, 2013, Dublin, Ireland. [PDF][slides]
  • A General Collaborative Filtering Framework based on Matrix Bordered Block Diagonal Forms
    Yongfeng Zhang, Min Zhang, Yiqun Liu and Shaoping Ma. In proceedings of the 24th ACM Conference on Hypertext and Social Media (HT 2013), May 1 - 3, 2013, Paris, France. [PDF]
  • A Unified Framework for Emotional Elements Extraction based on Finite State Matching Machine
    Yunzhi Tan, Yongfeng Zhang, Min Zhang, Yiqun Liu and Shaoping Ma. In Proceedings of the 2nd CCF Conference on Natural Language Processing and Chinese Computing (NLPCC 2013), Nov. 15 - 19, 2013, Chongqing, China. [PDF]
  • A New Criterion for Judging the Value of Knowledge Systems
    Yongfeng Zhang and Wei Dai. Journal of Literature and Art Studies (JLAS), Vol.3, No.1, 2013. [PDF]
  • Towards the Adaption to the Open Texture of Law
    Yu Li, Jing Zhang, and Yongfeng Zhang. In Proceedings of the 2013 International Conference on Complex Science Management and Education Science, Nov 23 - 24, Kunming, China, 2013. [PDF]

  • 2010

  • Investigating Characteristics of Non-click Behavior Using Query Logs
    Ting Yao, Min Zhang, Yiqun Liu, Shaoping Ma, Yongfeng Zhang, and Liyun Ru. In Proceedings of the 6th Asia Information Retrieval Societies Conference (AIRS 2010), December 1 - 3, Taipei, Taiwan. [PDF]

Books

  • Explainable Recommendation: A Survey and New Perspectives
    Yongfeng Zhang and Xu Chen. Foundations and Trends in Information Retrieval: Vol. 14, No. 1, pp 1-101. Now Publishers. ISBN: 9781680836585. [Website]
  • Explainable Recommendation: Theory and Applications
    Yongfeng Zhang. Tsinghua University Press. ISBN: 9787302531968. [Website]
  • Causal Explainable AI
    Shuyuan Xu, Yingqiang Ge and Yongfeng Zhang. Machine Learning for Causal Inference, Springer Cham. ISBN: 978-3-031-35050-4. [PDF]
  • Personalized Recommender Systems - Understanding the Users behind the System
    Yongfeng Zhang. In Z. Liu and A. Cui, editors, Big Data Intelligence, Publishing House of Electronics Industry, pp.130-163. ISBN: 9787121276484. [Website][Amazon]
  • Introduction to Explainable Artificial Intelligence
    Qiang Yang, Lixin Fan, Jun Zhu, Yixin Chen, Quanshi Zhang, Songchun Zhu, Dacheng Tao, Peng Cui, Shaohua Zhou, Qi Liu, Xuanjing Huang, Yongfeng Zhang. Publishing House of Electronics Industry. ISBN: 9787121431876. [Website]

Tutorials

  • Tutorial on Large Language Models for Recommendation
    Wenyue Hua, Lei Li, Shuyuan Xu, Li Chen, and Yongfeng Zhang. In Proceedings of the 17th ACM Conference on Recommender Systems (RecSys 2023), September 18 - 22, 2023, Singapore. [PDF][Slides][Website]
    Tutorial homepage: https://llmrecsys.github.io/
  • CIKM 2021 Tutorial on Fairness of Machine Learning in Recommender Systems
    Yunqi Li, Yingqiang Ge, Yongfeng Zhang. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM 2021), November 1 - 5, 2021, Gold Coast, Australia. [PDF]
    Tutorial homepage: https://fairness-tutorial.github.io/
  • Tutorial on Fairness of Machine Learning in Recommender Systems
    Yunqi Li, Yingqiang Ge, Yongfeng Zhang. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
    Tutorial homepage: https://fairness-tutorial.github.io/
  • IUI 2021 Tutorial on Conversational Recommendation Systems
    Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang. In Proceedings of the 26th International Conference on Intelligent User Interfaces. (IUI 2021), April 13 - 17, 2021. Online. [PDF]
    Tutorial homepage: https://zuohuif.github.io/RecSys2020ConvRecTutorial/, Tutorial Slides: download, Tutorial Video: click here to YouTube
  • WSDM 2021 Tutorial on Conversational Recommendation Systems
    Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining. (WSDM 2021), March 8 - 12, 2021. Online. [PDF]
    Tutorial homepage: https://zuohuif.github.io/RecSys2020ConvRecTutorial/, Tutorial Slides: download, Tutorial Video: click here to YouTube
  • Tutorial on Conversational Recommendation Systems
    Zuohui Fu, Yikun Xian, Yongfeng Zhang, Yi Zhang. In Proceedings of the Fourteenth ACM Conference on Recommender Systems (pp. 751-753). (RecSys 2020), September 22 - 26, 2020. Online. [PDF]
    Tutorial homepage: https://zuohuif.github.io/RecSys2020ConvRecTutorial/, Tutorial Slides: download, Tutorial Video: click here to YouTube
  • Tutorial on Explainable Recommendation and Search
    Yongfeng Zhang. In Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR 2019), October 2 - 5, 2019, Santa Clara, California. [PDF]
    Tutorial homepage: https://sites.google.com/view/ears-tutorial, Tutorial Slides: download
  • SIGIR 2019 Tutorial on Explainable Recommendation and Search
    Yongfeng Zhang, Jiaxin Mao, Qingyao Ai. In Proceedings of the 42th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
    Tutorial homepage: https://sites.google.com/view/ears-tutorial, Tutorial Slides: download
  • WWW'19 Tutorial on Explainable Recommendation and Search
    Yongfeng Zhang, Jiaxin Mao, Qingyao Ai. In Proceedings of the Web Conference 2019 (WWW 2019), May 13 - 17, 2019, SF, USA. [PDF]
    Tutorial homepage: https://sites.google.com/view/ears-tutorial, Tutorial Slides: download

Workshops

  • CSR 2021: The 1st International Workshop on Causality inSearch and Recommendation
    Yongfeng Zhang, Xu Chen, Yi Zhang, Xianjie Chen. In Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021), July 11 - 15, 2021, Virtual Event, Canada. [PDF]
    Workshop homepage: https://csr21.github.io/
  • The 1st International Workshop on Machine Reasoning: International Machine Reasoning Conference (MRC 2021)
    Yongfeng Zhang, Min Zhang, Hanxiong Chen, Xu Chen, Xianjie Chen, Chuang Gan, Tong Sun, Xin Luna Dong. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021), March 8 - 12, 2021, Online. [PDF]
    Workshop homepage and proceedings: http://mrc2021.github.io/
  • EARS 2020: The 3rd International Workshop on ExplainAble Recommendation and Search
    Yongfeng Zhang, Xu Chen, Yi Zhang, Min Zhang, Chirag Shah. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), July 25 - 30, 2020, Xi'an, China. [PDF]
    Workshop homepage and proceedings: http://ears2020.github.io/
  • EARS 2019: The 2nd International Workshop on ExplainAble Recommendation and Search
    Yongfeng Zhang, Yi Zhang, Min Zhang, Chirag Shah. In Proceedings of the 42th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019), July 21 - 25, 2019, Paris, France. [PDF]
    Workshop homepage and proceedings: http://ears2019.github.io/
  • Report on EARS'18: 1st International Workshop on ExplainAble Recommendation and Search
    Yongfeng Zhang, Yi Zhang, Min Zhang. ACM SIGIR Forum, Volume 52, Issue 2, 2018. [PDF]
  • SIGIR 2018 Workshop on ExplainAble Recommendation and Search (EARS 2018)
    Yongfeng Zhang, Yi Zhang, Min Zhang. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018), July 8 - 12, 2018, Ann Arbor, Michigan, USA. [PDF]
    Workshop homepage and proceedings: http://ears2018.github.io/
  • IFUP: Workshop on Multi-dimensional Information Fusion for User Modeling and Personalization
    Feida Zhu, Yongfeng Zhang, Neil Yorke-Smith, Guibing Guo, Xu Chen. In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM 2018), February 5 - 9, 2018, Los Angeles, California, USA. [PDF]

Technical Reports

  • When AI meets the Tango: The 24th International Joint Conference on Artificial Intelligence (in Chinese)
    Yongfeng Zhang, Xin Li, Jie Tang, Min Zhang. In China Computer Federation (CCF) Communications. Volume 11, Issue 09, 2015. [PDF].
  • Review of the 24th International Conference on World Wide Web (in Chinese)
    Yongfeng Zhang, Yiqun Liu, Jie Tang. In China Computer Federation (CCF) Communications. Volume 11, Issue 07, 2015. [PDF].
  • Time Series Analysis
    Yongfeng Zhang. Technical Report in State Key Laboratory of Intelligent Technology and Systems, Tsinghua University. 2014-05-05. [slides].
  • A Suervey of Recommender Systems
    Yongfeng Zhang. Technical Report in State Key Laboratory of Intelligent Technology and Systems, Tsinghua University. 2012-04-23. [PDF][slides].

Thesis

  • Explainable Recommendation - Theory and Applications
    Yongfeng Zhang. Dissertation submitted to Tsinghua University for the degree of Doctor of Philosophy in Computer Science (Jun 2016)
    Advisors: Shaoping Ma, Min Zhang, Yiqun Liu
    2017 Chinese Association for Artificial Intelligence (CAAI) Best PhD Dissertation Award. [PDF]