Pan Li

Research

Journal Publications

  1. Pan Li, Alexander Tuzhilin, “A Dynamical System Model for Exploring User Trajectories in Recommender Systems”, Forthcoming at IEEE Transactions on Knowledge and Data Engineering (TKDE)
  2. Pan Li, Alexander Tuzhilin, “Deep Pareto Reinforcement Learning for Multi-Objective Recommender Systems”, Forthcoming at MIS Quarterly (MISQ)
  3. Pan Li, Alexander Tuzhilin, “When Variety-Seeking Meets Unexpectedness: Incorporating Variety-Seeking Behavior into Design of Unexpected Recommender Systems”, Information System Research (ISR) Volume: 35 Issue: 3, pp. 1257-1273 (2023)
  4. Pan Li, Maofei Que, Alexander Tuzhilin, “Dual Contrastive Learning for Efficient Static Feature Representation in Recommender System”, IEEE Transactions on Knowledge and Data Engineering (TKDE) Volume: 36 Issue: 2, pp. 544-555 (2023)
  5. Moshe Unger, Pan Li, Shahana Sen, Alexander Tuzhilin, “Reconstructing Universal Embeddings of Customers from Domain-Specific Embeddings”, ACM Transactions on Management Information Systems (TMIS) Volume 14, Issue 2, Article No. 20, pp. 1–30 (2023)
  6. Pan Li, Alexander Tuzhilin, “Dual Metric Learning for Effective and Efficient Cross-Domain Recommendations”, IEEE Transactions on Knowledge and Data Engineering (TKDE) Volume: 35 Issue: 1, pp. 321-334 (2023)
  7. Pan Li, Brian Brost, Alexander Tuzhilin, “Adversarial Learning for Cross-Domain Recommendations”, ACM Transactions on Intelligent Systems and Technology (TIST) Volume 14, Issue 1, Article No. 5, pp. 1–25 (2022)
  8. Pan Li, Alexander Tuzhilin, “Learning Latent Multi-Criteria Ratings from User Reviews for Recommendations”, IEEE Transactions on Knowledge and Data Engineering (TKDE), Volume: 34 Issue: 8, pp. 3854-3866 (2022)
  9. Pan Li, Alexander Tuzhilin, “Latent Unexpected Recommendations”, ACM Transactions on Intelligent Systems and Technology (TIST), 11(6), pp. 1-25 (2020)
  10. Chen Zhu, Hengshu Zhu, Hui Xiong, Chao Ma, Fang Xie, Pengliang Ding, Pan Li, “Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning”, ACM Transactions on Management Information Systems (TMIS) 9, no. 3: 1-17 (2018)

Journal Papers Under Review

  1. Pan Li, Jie Xu, D. J. Wu, Min Ding, “When Interpretations and Predictions Help Each Other: A Novel Dual Learning Framework and Its Application in Visual Analytics”, Under Fourth-Round Review at Information System Research (ISR) (after Major Revision)
  2. Moshe Unger*, Pan Li*, Maxime Cohen, Brian Brost, Alexander Tuzhilin, “Bridging Listeners with Artists: Deep Multi-Objective Multi-Stakeholder Music Recommendations”, Under Third-Round Review at Management Science (MS) (*equal contribution, after Major Revision)
  3. Yuyan Wang, Pan Li, Minmin Chen, “Can Explanations Improve Recommendations? A Joint Optimization with LLM Reasoning”, Major Revision at Management Science (MS)
  4. Pan Li, “All Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanations with Large Language Models”, Under Review at MIS Quarterly (MISQ)

Working Papers

  1. “I Want to Know More!: Measuring Evoked Curiosity to Recommend What Consumers Wonder About” (with Alexander Tuzhilin)
  2. “Modeling Hierarchical User Exploration for Improving Long-Term Performance in Recommender Systems” (with Yuyan Wang and Minmin Chen)
  3. “Tuning towards Fairness: Conditional Disentangled Image Generation” (with Yi Gan, Jie Xu, D.J. Wu, and Min Ding)
  4. “Optimizing Federated Cross-Domain Recommendation with Efficient LLM Adaptation” (with Xing Zhao)
  5. “IV Filter: Discovering Interpretable Instrumental Variables from Latent Identification Signals with Large Language Models” (with Shuang Gao)

Conference Publications

  1. Shui Liu, Mingyuan Tao, Maofei Que, Pan Li and Zhuoran Zhuang, “APPNet: Automatic Feature Partitioning-Based Parameter Personalized Network for Conversion Prediction in E-commerce”, Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM 2026)
    Full Paper with Oral Presentation; Acceptance Rate: 16.3%
  2. Xuanzhang Liu, Jianglun Feng, Zhuoran Zhuang, Junzhe Zhao, Maofei Que, Jieting Li, Dianlei Wang, Hao Tong, Ye Chen and Pan Li, “CoDA: A Context-Decoupled Hierarchical Agent with Reinforcement Learning”, Proceedings of the 19th ACM International Conference on Web Search and Data Mining (WSDM 2026)
    Full Paper with Oral Presentation; Acceptance Rate: 16.3%
  3. Chen Wang, Mingdai Yang, Zhiwei Liu, Pan Li, Linsey Pang, Qingsong Wen and Philip Yu, “AGP: Auto-Guided Prompt Refinement for Personalized Reranking in Recommender Systems”, Third Workshop on Generative AI for Recommender Systems and Personalization (GenAIRecP@WSDM 2026)
  4. Shui Liu, Mingyuan Tao, Maofei Que, Pan Li, Dong Li, Shenghua Ni and Zhuoran Zhuang, “NAM: A Normalization Attention Model for Personalized Product Search In Fliggy”, Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2025)
    Short Paper with Poster Presentation; Acceptance Rate: 27.5%
  5. Pan Li, Zhichao Jiang, Maofei Que, Yao Hu, Alexander Tuzhilin, “Dual Attentive Sequential Learning for Cross Domain Click-Through Rate Prediction”, Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2021)
    Full Paper with Oral Presentation; Acceptance Rate: 15.4%
  6. Pan Li, Maofei Que, Zhichao Jiang, Yao Hu, Alexander Tuzhilin, “PURS: Personalized Unexpected Recommender System for Improving User Satisfaction”, Proceedings of the 14th ACM Conference on Recommender System (RecSys 2020)
    Full Paper with Oral Presentation; Acceptance Rate: 18%
  7. Pan Li, Alexander Tuzhilin, “DDTCDR: Deep Dual Transfer Cross Domain Recommendation”, Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM 2020)
    Full Paper with Oral Presentation; Acceptance Rate: 15%
  8. Pan Li, Alexander Tuzhilin, “Towards Controllable and Personalized Review Generation”, Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019)
    Full Paper with Poster Presentation; Acceptance Rate: 24.6%
  9. Pan Li, Alexander Tuzhilin, “Latent Multi-Criteria Ratings for Recommendations”, Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019)
    Short Paper with Poster Presentation; Acceptance Rate: 19%
  10. Pan Li, Alexander Tuzhilin, “Latent Modeling of Unexpectedness for Recommendations”, Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019)
    Late-Breaking Result Track Paper with Poster Presentation; Acceptance Rate: 31%
  11. Tong Xu, Hengshu Zhu, Chen Zhu, Pan Li, Hui Xiong, “Measuring the popularity of job skills in recruitment market: A multi-criteria approach”, Proceedings of Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018)
    Full Paper with Poster Presentation; Acceptance Rate: 24.6%