Yi Fang
Sant Clara University
500 El Camino Real
Santa Clara, CA 95053

Office: Bergin 110
Email: yfang@scu.edu

Contact Information >

(see Google Scholar for up-to-date publication list)

• Xuyang Wu, Jinming Nian, Ting-Ruen Wei, Zhiqiang Tao, Hsin-Tai Wu, and Yi Fang. Does Reasoning Introduce Bias? A Study of Social Bias Evaluation and Mitigation in LLM Reasoning. The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.
  


• Xuyang Wu, Yuan Wang, Hsin-Tai Wu, Zhiqiang Tao, and Yi Fang. Evaluating Fairness in Large Vision-Language Models Across Diverse Demographic Attributes and Prompts. The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2025.
  


• Xuyang Wu, Shuowei Li, Hsin-Tai Wu, Zhiqiang Tao, Yi Fang. Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation Systems. The 31st International Conference on Computational Linguistics (COLING), 2025.
  


• Jinming Nian, Zhiyuan Peng, Qifan Wang, Yi Fang. W-RAG: Weakly Supervised Dense Retrieval in RAG for Open-domain Question Answering. In Proceedings of the International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval (ICTIR), 2025.
  


• Zhiyuan Peng, Jinming Nian, Alexandre Evfimievski, Yi Fang. ELOQ: Resources for Enhancing LLM Detection of Out-of-Scope Questions. In Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2025.
  


• Haowei Liu, Xuyang Wu, Guohao Sun, Zhiqiang Tao, Yi Fang. RaCT: Ranking-aware Chain-of-Thought Optimization for LLMs. In Proceedings of the 3rd International ACM SIGIR Conference on Research and Development in Information Retrieval - Asia/Pacific (SIGIR-AP), 2025.
  


• Xuyang Wu, Ajit Puthenputhussery, Hongwei Shang, Changsung Kang, Yi Fang. Meta Learning to Rank for Sparsely Supervised Queries. In ACM Transactions on Information Systems (TOIS), 2025.
  


• Li Yang, Qifan Wang, Jianfeng Chi, Jiahao Liu, Jingang Wang, Fuli Feng, Zenglin Xu, Yi Fang, Lifu Huang, Dongfang Liu. EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction. In Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
  


• Cheng Han, Qifan Wang, Sohail A. Dianat, Majid Rabbani, Raghuveer M. Rao, Yi Fang, Qiang Guan, Lifu Huang, Dongfang Liug. AMD: Automatic Multi-step Distillation of Large-scale Vision Models. In The 18th European Conference on Computer Vision (ECCV), 2025.
  


• Yi Fang, Ashudeep Singh, Zhiqiang Tao. Fairness in Search Systems. Foundations and Trends in Information Retrieval, 2024.
  


• Yuan Wang, Zhiqiang Tao, Yi Fang. A Unified Meta-learning Framework for Fair Ranking with Curriculum Learning. In IEEE Transactions on Knowledge & Data Engineering (TKDE), 2024.
  


• Yuan Wang, Xuyang Wu, Hsin-Tai Wu, Zhiqiang Tao, Yi Fang. Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers. In Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.
  


• Guohao Sun, Yue Bai, Xueying Yang, Yi Fang, Yun Fu, Zhiqiang Tao. Aligning Out-of-Distribution Web Images and Caption Semantics via Evidential Learning. In Proceedings of the Web Conference (WWW), 2024.
  


• Hannah Covington, Brian Woo-Shem, Chenli Wang, Thomas Roth, Cuong Nguyen, Yuhong Liu, Yi Fang, Hohyun Lee. Method for Evaluating Fairness of Electricity Tariffs with regard to Income Level of Residential Buildings. In Applied Energy, 2024.
  


• Yuan Wang, Peifeng Yin, Zhiqiang Tao, Hari Venkatesan, Jin Lai, Yi Fang, PJ Xiao. An Empirical Study of Selection Bias in Pinterest Ads Retrieval. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
  


• Zhiyuan Peng, Vachik Dave, Nicole McNabb, Rahul Sharnagat, Alessandro Magnani, Ciya Liao, Yi Fang, Sravanthi Rajanala. Entity-aware Multi-task Learning for Query Understanding at Walmart. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023.
  


• Xiaoxiao Shang, Ye Chen, Yi Fang, Yuhong Liu, Subramaniam Vincent. AMICA: Alleviating Misinformation for Chinese Americans. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023.
  


• Yi Fang, Hongfu Liu, Zhiqiang Tao, Mikhail Yurochkin. Fairness of Machine Learning in Search Engines. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM), 2022. (Tutorial Slides)
  


• Nagaarchana Godavarthy, Yuan Wang, Travis Ebesu, Un Suthee, Min Xie, Yi Fang. Learning User Preferences Through Online Conversations via Personalized Memory Transfer. In Information Retrieval Journal, 2022.
  


• Xiaoxiao Shang, Zhiyuan Peng, Qiming Yuan, Sabiq Khan, Lauren Xie, Yi Fang and Subramaniam Vincent. Two-sided Rank Consistent Ordinal Regression for Interpretable Music Key Recommendation. In Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR), 2022.
  


• Xiaoxiao Shang, Zhiyuan Peng, Qiming Yuan, Sabiq Khan, Lauren Xie, Yi Fang and Subramaniam Vincent. DIANES: A DEI Audit Toolkit for News Sources. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022.
  


• Yuan Wang, Zhiqiang Tao, Yi Fang. A Meta-learning Approach to Fair Ranking. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022.
  


• Xuyang Wu, Alessandro Magnani, Suthee Chaidaroon, Ajit Puthenputhussery, Ciya Liao, and Yi Fang. A Multi-task Learning Framework for Product Ranking with BERT. In Proceedings of the Web Conference (WWW), 2022.
  


• Qifan Wang, Yi Fang, Anirudh Ravula, Fuli Feng, Xiaojun Quan, and Dongfang Liu. WebFormer: The Web-page Transformer for Structure Information Extraction. In Proceedings of the Web Conference (WWW), 2022.
  


• Qifan Wang, Yi Fang, Anirudh Ravula, Ruining He, Bin Shen, Jingang Wang, Xiaojun Quan, Dongfang Liu. Deep Partial Multiplex Network Embedding. In Companion Proceedings of the Web Conference 2022 (Workshop on Graph Learning), 2022.
  


• Zhiyuan Peng, Behnoush Abdollahi, Min Xie, Yi Fang. Multi-label Classification of Short Texts with Label Correlated Recurrent Neural Networks. In Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval (ICTIR), 2021.
  


• Yuan Wang, Shigeki Tanaka, Keita Yokoyama, Hsin-Tai Wu, Yi Fang. Karaoke Key Recommendation Via Personalized Competence-Based Rating Prediction. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
  


• Yuan Wang, Chenwei Wang, Yinan Ling, Keita Yokoyama, Hsin-Tai Wu, Yi Fang. Leveraging an Efficient and Semantic Location Embedding to Seek New Ports of Bike Share Services. In IEEE International Conference on Big Data, 2020.
  


• Boli Fang, Miao Jiang, Pei-Yi Cheng, Jerry Shen, Yi Fang. Achieving Outcome Fairness in Machine Learning Models for Social Decision Problems. In the 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.
  


• Suthee Chaidaroon, Dae Hoon Park, Yi Chang, Yi Fang. node2hash: Graph aware Deep Semantic Text Hashing. In Information Processing & Management (IPM), 2019.
  


• Travis Ebesu, Bin Shen, Yi Fang. Collaborative Memory Network for Recommendation Systems. In Proceedings of the 41th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2018.
  


• Suthee Chaidaroon, Travis Ebesu, Yi Fang. Deep Semantic Text Hashing with Weak Supervision. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2018.
  


• Yogesh Jhamb, Travis Ebesu, Yi Fang. Attentive Contextual Denoising Autoencoder for Recommendation. In Proceedings of the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), 2018.
  


• Miao Jiang, Yi Fang, Huangming Xie, Jike Chong, Meng Meng. User click prediction for personalized job recommendation. In World Wide Web Journal, Springer, 2018.
  


• Haibing Lu, Wendong Zhu, Manoochehr Ghiassi, Yi Fang, Hong Yuan, Xiaoyun He. Fault-Tolerant Tile Mining. In Expert Systems With Applications, Elsevier, 2018.
  


• Suthee Chaidaroon, Yi Fang. Variational Deep Semantic Hashing for Text Documents. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017.
  


• Travis Ebesu, Yi Fang. Neural Citation Network for Context-Aware Citation Recommendation. In Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017.
  


• Travis Ebesu, Yi Fang. Neural Semantic Personalized Ranking for Item Cold-Start Recommendation. In Information Retrieval Journal (IRJ), Springer, 2017.
  


• Mengwen Liu, Yi Fang, Alex G. Choulos, Dae Hoon Park, and Xiaohua Hu. Product Review Summarization through Question Retrieval and Diversification. In Information Retrieval Journal (IRJ), Springer, 2017.
  


• Zhongchen Miao, Kai Chen, Yi Fang, Jianhua He, Yi Zhou, Wenjun Zhang, Hongyuan Zha. Cost-effective Online Trending Topic Detection and Popularity Prediction in Microblogging. In ACM Transactions on Information Systems (TOIS), Volume 35, Issue 3, 2017.
  


• Yogesh Jhamb, Yi Fang A Dual-Perspective Latent Factor Model for Group-Aware Social Event Recommendation. In Information Processing and Management (IPM), Elsevier, 2017.
  


• Mengwen Liu, Wanying Ding, Dae Hoon Park, Yi Fang, Rui Yan, Xiaohua Hu. Which Used Product is More Sellable? A Time-Aware Approach. In Information Retrieval Journal (IRJ), Springer, 2017.
  


• Mengwen Liu, Yi Fang, Dae Hoon Park, Xiaohua Hu, Zhengtao Yu. Retrieving Non-Redundant Questions to Summarize a Product Review. In Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2016.
  


• Dae Hoon Park, Yi Fang, Mengwen Liu, and Chengxiang Zhai. Mobile App Retrieval for Social Media Users via Inference of Implicit Intent in Social Media Text. . In Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM), 2016.
  


• Hui Wu, Yi Fang, Huming Wu, and Shenhong Zhu. Diversifying Trending Topic Discovery via Semidefinite Programming. In IEEE International Conference on Big Data, 2016.
  


• Yi Fang, Mengwen Liu. A Unified Energy-based Framework for Learning to Rank . In Proceedings of the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), 2016.
  


• Yi Fang, Archana Godavarthy, Haibing Lu. A Utility Maximization Framework for Privacy Preservation of User Generated Content. In Proceedings of the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), 2016.
  


• Archana Godavarthy, Yi Fang. Cross-Language Microblog Retrieval using Latent Semantic Modeling. In Proceedings of the ACM SIGIR International Conference on the Theory of Information Retrieval (ICTIR), 2016.