| 2025 | ACL | Customizing In-context Learning for Dynamic Interest Adaption in LLM-based Recommendation. | Keqin Bao, Ming Yan, Yang Zhang, Jizhi Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2025 | ACL | K-order Ranking Preference Optimization for Large Language Models. | Shihao Cai, Chongming Gao, Yang Zhang, Wentao Shi, Jizhi Zhang, Keqin Bao, Qifan Wang, Fuli Feng |
| 2025 | EMNLP | Leveraging Unpaired Feedback for Long-Term LLM-based Recommendation Tuning. | Jizhi Zhang, Chongming Gao, Wentao Shi, Xi-Lin Chen, Jingang Wang, Xunliang Cai, Fuli Feng |
| 2025 | WWW | Debias Can Be Unreliable: Mitigating Bias in Evaluating Debiasing Recommendation. | Chengbing Wang, Wentao Shi, Jizhi Zhang, Wenjie Wang, Hang Pan, Fuli Feng |
| 2025 | WWW | Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendation. | Chengbing Wang, Yang Zhang, Fengbin Zhu, Jizhi Zhang, Tianhao Shi, Fuli Feng |
| 2025 | SIGIR | Navigating Large Language Models for Recommendation: From Architecture to Learning Paradigms and Deployment. | Xinyu Lin, Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng |
| 2025 | SIGIR | Agentic Feedback Loop Modeling Improves Recommendation and User Simulation. | Shihao Cai, Jizhi Zhang, Keqin Bao, Chongming Gao, Qifan Wang, Fuli Feng, Xiangnan He |
| 2025 | SIGIR | Fair Recommendation with Biased-Limited Sensitive Attribute. | Jizhi Zhang, Haoyu Shen, Tianhao Shi, Keqin Bao, Xin Chen, Yang Zhang, Fuli Feng |
| 2024 | CIKM | Learnable Item Tokenization for Generative Recommendation. | Wenjie Wang, Honghui Bao, Xinyu Lin, Jizhi Zhang, Yongqi Li, Fuli Feng, See-Kiong Ng, Tat-Seng Chua |
| 2024 | EMNLP | Decoding Matters: Addressing Amplification Bias and Homogeneity Issue in Recommendations for Large Language Models. | Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, Fuli Feng |
| 2024 | EMNLP | GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation. | Shihao Cai, Keqin Bao, Hangyu Guo, Jizhi Zhang, Jun Song, Bo Zheng |
| 2024 | ICDE | BSL: Understanding and Improving Softmax Loss for Recommendation. | Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang |
| 2024 | WWW | Item-side Fairness of Large Language Model-based Recommendation System. | Meng Jiang, Keqin Bao, Jizhi Zhang, Wenjie Wang, Zhengyi Yang, Fuli Feng, Xiangnan He |
| 2024 | WWW | Large Language Models for Recommendation: Progresses and Future Directions. | Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2024 | SIGIR | Large Language Models for Recommendation: Past, Present, and Future. | Keqin Bao, Jizhi Zhang, Xinyu Lin, Yang Zhang, Wenjie Wang, Fuli Feng |
| 2024 | SIGIR | Large Language Models are Learnable Planners for Long-Term Recommendation. | Wentao Shi, Xiangnan He, Yang Zhang, Chongming Gao, Xinyue Li, Jizhi Zhang, Qifan Wang, Fuli Feng |
| 2024 | SIGIR | Fair Recommendations with Limited Sensitive Attributes: A Distributionally Robust Optimization Approach. | Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He |
| 2024 | SIGIR | Diffusion Models for Generative Outfit Recommendation. | Yiyan Xu, Wenjie Wang, Fuli Feng, Yunshan Ma, Jizhi Zhang, Xiangnan He |
| 2023 | CIKM | Popularity-aware Distributionally Robust Optimization for Recommendation System. | Jujia Zhao, Wenjie Wang, Xinyu Lin, Leigang Qu, Jizhi Zhang, Tat-Seng Chua |
| 2023 | EMNLP | Robust Prompt Optimization for Large Language Models Against Distribution Shifts. | Moxin Li, Wenjie Wang, Fuli Feng, Yixin Cao, Jizhi Zhang, Tat-Seng Chua |
| 2023 | RecSys | TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation. | Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2023 | RecSys | Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation. | Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He |
| 2023 | WWW | On the Theories Behind Hard Negative Sampling for Recommendation. | Wentao Shi, Jiawei Chen, Fuli Feng, Jizhi Zhang, Junkang Wu, Chongming Gao, Xiangnan He |
| 2023 | SIGIR | A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. | Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang |
| 2021 | ACL | Empowering Language Understanding with Counterfactual Reasoning. | Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua |