On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (IJCAI, 2022)

A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction. - Quanyu Dai; Haoxuan Li 001; Peng Wu 012; Zhenhua Dong; Xiao-Hua Zhou; Rui Zhang 079; Rui Zhang 003; Jie Sun 007 (KDD, 2022)

Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. - Sihao Ding 003; Peng Wu 012; Fuli Feng; Yitong Wang; Xiangnan He 001; Yong Liao; Yongdong Zhang 001 (KDD, 2022)

Accepted Tutorials at The Web Conference 2022. - Riccardo Tommasini 001; Senjuti Basu Roy; Xuan Wang 008; Hongwei Wang; Heng Ji 001; Jiawei Han 001; Preslav Nakov; Giovanni Da San Martino; Firoj Alam; Markus Schedl; Elisabeth Lex; Akash Bharadwaj; et al. (WWW (Companion Volume), 2022)

Causal Analysis Framework for Recommendation. - Peng Wu 012; Haoxuan Li 001; Yuhao Deng; Wenjie Hu; Quanyu Dai; Zhenhua Dong; Jie Sun 007; Rui Zhang; Xiao-Hua Zhou (CoRR, 2022)

A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems. - Yan Lyu; Sunhao Dai; Peng Wu 012; Quanyu Dai; Yuhao Deng; Wenjie Hu; Zhenhua Dong; Jun Xu 001; Shengyu Zhu 001; Xiao-Hua Zhou (CoRR, 2022)

Doubly Robust Collaborative Targeted Learning for Recommendation on Data Missing Not at Random. - Peng Wu 012; Haoxuan Li 001; Yan Lyu; Xiao-Hua Zhou (CoRR, 2022)

Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. - Haoxuan Li 001; Chunyuan Zheng 001; Xiao-Hua Zhou; Peng Wu 012 (CoRR, 2022)

Multiple Robust Learning for Recommendation. - Haoxuan Li 001; Quanyu Dai; Yuru Li; Yan Lyu; Zhenhua Dong; Xiao-Hua Zhou; Peng Wu 012 (AAAI, 2023)

TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. - Haoxuan Li 001; Yan Lyu; Chunyuan Zheng 001; Peng Wu 012 (ICLR, 2023)

StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. - Haoxuan Li 001; Chunyuan Zheng 001; Peng Wu 012 (ICLR, 2023)

Propensity Matters: Measuring and Enhancing Balancing for Recommendation. - Haoxuan Li 001; Yanghao Xiao; Chunyuan Zheng 001; Peng Wu 012; Peng Cui 001 (ICML, 2023)

Trustworthy Policy Learning under the Counterfactual No-Harm Criterion. - Haoxuan Li 001; Chunyuan Zheng 001; Yixiao Cao; Zhi Geng; Yue Liu; Peng Wu 012 (ICML, 2023)

Who Should Be Given Incentives? Counterfactual Optimal Treatment Regimes Learning for Recommendation. - Haoxuan Li 001; Chunyuan Zheng 001; Peng Wu 012; Kun Kuang; Yue Liu; Peng Cui 001 (KDD, 2023)

Fairly Recommending with Social Attributes: A Flexible and Controllable Optimization Approach. - Jinqiu Jin; Haoxuan Li 001; Fuli Feng; Sihao Ding 003; Peng Wu 012; Xiangnan He 001 (NeurIPS, 2023)

Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. - Haoxuan Li 001; Kunhan Wu; Chunyuan Zheng 001; Yanghao Xiao; Hao Wang 049; Zhi Geng; Fuli Feng; Xiangnan He 001; Peng Wu 012 (NeurIPS, 2023)

Causal Recommendation: Progresses and Future Directions. - Wenjie Wang 007; Yang Zhang 072; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (SIGIR, 2023)

Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations. - Haoxuan Li 001; Yanghao Xiao; Chunyuan Zheng 001; Peng Wu 012 (WWW, 2023)

Uncovering the Propensity Identification Problem in Debiased Recommendations. - Honglei Zhang; Shuyi Wang; Haoxuan Li 001; Chunyuan Zheng 001; Xu Chen 017; Li Liu 001; Shanshan Luo; Peng Wu 012 (ICDE, 2024)

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference. - Haoxuan Li 001; Chunyuan Zheng 001; Sihao Ding 003; Peng Wu 012; Zhi Geng; Fuli Feng; Xiangnan He 001 (ICLR, 2024)

Debiased Collaborative Filtering with Kernel-Based Causal Balancing. - Haoxuan Li 001; Chunyuan Zheng 001; Yanghao Xiao; Peng Wu 012; Zhi Geng; Xu Chen 017; Peng Cui 001 (ICLR, 2024)

Policy Learning for Balancing Short-Term and Long-Term Rewards. - Peng Wu 012; Ziyu Shen; Feng Xie 002; Zhongyao Wang; Chunchen Liu; Yan Zeng 002 (ICML, 2024)

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering. - Haoxuan Li 001; Chunyuan Zheng 001; Shuyi Wang; Kunhan Wu; Eric Hao Wang; Peng Wu 012; Zhi Geng; Xu Chen 017; Xiao-Hua Zhou (ICML, 2024)

Local Causal Structure Learning in the Presence of Latent Variables. - Feng Xie 002; Zheng Li; Peng Wu 012; Yan Zeng 002; Chunchen Liu; Zhi Geng (ICML, 2024)

Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards. - Qinwei Yang; Xueqing Liu; Yan Zeng 002; Ruocheng Guo; Yang Liu 018; Peng Wu 012 (NeurIPS, 2024)

Treatment Effect Estimation for User Interest Exploration on Recommender Systems. - Jiaju Chen; Wenjie Wang 007; Chongming Gao; Peng Wu 012; Jianxiong Wei; Qingsong Hua (SIGIR, 2024)

Proactive Recommendation in Social Networks: Steering User Interest via Neighbor Influence. - Hang Pan 006; Shuxian Bi; Wenjie Wang 007; Haoxuan Li 001; Peng Wu 012; Fuli Feng; Xiangnan He 001 (CoRR, 2024)

Optimal Policy Adaptation under Covariate Shift. - Xueqing Liu; Qinwei Yang; Zhaoqing Tian; Ruocheng Guo; Peng Wu 012 (CoRR, 2025)

Learning Counterfactual Outcomes Under Rank Preservation. - Peng Wu 012; Haoxuan Li 001; Chunyuan Zheng 001; Yan Zeng 002; Jiawei Chen; Yang Liu 018; Ruocheng Guo; Kun Zhang 001 (CoRR, 2025)

Identification and Estimation of Long-Term Treatment Effects with Monotone Missing. - Qinwei Yang; Ruocheng Guo; Shasha Han; Peng Wu 012 (CoRR, 2025)

Confounded Causal Imitation Learning with Instrumental Variables. - Yan Zeng 002; Shenglan Nie; Feng Xie 002; Libo Huang; Peng Wu 012; Zhi Geng (CoRR, 2025)