RLT: Residual-Loop Training in Collaborative Filtering for Combining Factorization and Global-Local Neighborhood. - Lei Li 042; Weike Pan; Li Chen 009; Zhong Ming 001 (ICWS, 2018)

Context-Aware Co-attention Neural Network for Service Recommendations. - Lei Li 042; Ruihai Dong; Li Chen 009 (ICDE Workshops, 2019)

Generate Neural Template Explanations for Recommendation. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (CIKM, 2020)

Towards Controllable Explanation Generation for Recommender Systems via Neural Template. - Lei Li 042; Li Chen 009; Yongfeng Zhang (WWW (Companion Volume), 2020)

Personalized Transformer for Explainable Recommendation. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (ACL/IJCNLP (1), 2021)

EXTRA: Explanation Ranking Datasets for Explainable Recommendation. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (SIGIR, 2021)

Learning to Explain Recommendations. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (CoRR, 2021)

CAESAR: context-aware explanation based on supervised attention for service recommendations. - Lei Li 042; Li Chen 009; Ruihai Dong (J. Intell. Inf. Syst., 2021)

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

Augmenting Legal Judgment Prediction with Contrastive Case Relations. - Dugang Liu; Weihao Du; Lei Li 042; Weike Pan; Zhong Ming 001 (COLING, 2022)

TUR: Utilizing Temporal Information to Make Unexpected E-Commerce Recommendations. - Yongxin Ni; Ningxia Wang; Li Chen 009; Rui Chen 012; Lei Li 042 (WISE, 2022)

Effects of Feature-Based Explanation and Its Output Modality on User Satisfaction With Service Recommender Systems. - Zhirun Zhang; Li Chen 009; Tonglin Jiang; Yutong Li; Lei Li 042 (Frontiers Big Data, 2022)

Prompt Distillation for Efficient LLM-based Recommendation. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (CIKM, 2023)

Tutorial on Large Language Models for Recommendation. - Wenyue Hua; Lei Li 042; Shuyuan Xu; Li Chen 009; Yongfeng Zhang (RecSys, 2023)

On the Relationship between Explanation and Recommendation: Learning to Rank Explanations for Improved Performance. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (ACM Trans. Intell. Syst. Technol., 2023)

Personalized Prompt Learning for Explainable Recommendation. - Lei Li 042; Yongfeng Zhang; Li Chen 009 (ACM Trans. Inf. Syst., 2023)

Large Language Models for Generative Recommendation: A Survey and Visionary Discussions. - Lei Li 042; Yongfeng Zhang; Dugang Liu; Li Chen 009 (LREC/COLING, 2024)

EARL: Workshop on Evaluating and Applying Recommendation Systems with Large Language Models. - Irene Li; Ruihai Dong; Lei Li 042; Li Chen 009 (RecSys, 2024)