{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:29:09Z","timestamp":1773246549260,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":58,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,8,3]]},"DOI":"10.1145\/3711896.3736832","type":"proceedings-article","created":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T20:54:17Z","timestamp":1754254457000},"page":"3808-3818","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Addressing Correlated Latent Exogenous Variables in Debiased Recommender Systems"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-3555-7825","authenticated-orcid":false,"given":"Shuqiang","family":"Zhang","sequence":"first","affiliation":[{"name":"Dalhousie University, Halifax, Nova Scotia, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7746-2620","authenticated-orcid":false,"given":"Yuchao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing University of Chemical Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-5792-2097","authenticated-orcid":false,"given":"Jinkun","family":"Chen","sequence":"additional","affiliation":[{"name":"Dalhousie University, Halifax, Nova Scotia, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-0405-7301","authenticated-orcid":false,"given":"Haochen","family":"Sui","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,8,3]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE53745.2022.00211"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462919"},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3522672"},{"key":"e_1_3_2_2_4_1","volume-title":"Improving Data-Driven Inferential Sensor Modeling by Industrial Knowledge: A Bayesian Perspective","author":"Chen Zhichao","year":"2024","unstructured":"Zhichao Chen, Hao Wang, Zhihuan Song, and Zhiqiang Ge. 2024. Improving Data-Driven Inferential Sensor Modeling by Industrial Knowledge: A Bayesian Perspective. IEEE Transactions on Systems, Man, and Cybernetics: Systems(2024)."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539270"},{"key":"e_1_3_2_2_6_1","volume-title":"Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining.","author":"Ding Sihao","year":"2022","unstructured":"Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, and Yongdong Zhang. 2022. Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3511808.3557220"},{"key":"e_1_3_2_2_8_1","volume-title":"Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. In International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Guo Siyuan","year":"2021","unstructured":"Siyuan Guo, Lixin Zou, Yiding Liu, Wenwen Ye, Suqi Cheng, Shuaiqiang Wang, Hechang Chen, Dawei Yin, and Yi Chang. 2021. Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. In International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_9_1","unstructured":"Mingming Ha Taoxuewen Wenfang Lin Qiongxu Ma Wujiang Xu and Linxun Chen. 2024. Fine-Grained Dynamic Framework for Bias-Variance Joint Optimization on Data Missing Not at Random. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_10_1","unstructured":"Joseph Y Halpern and Evan Piermont. 2024. Subjective Causality. arXiv preprint arXiv:2401.10937(2024)."},{"key":"e_1_3_2_2_11_1","volume-title":"Neural Collaborative Filtering. In International Conference on World Wide Web.","author":"He Xiangnan","year":"2017","unstructured":"Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017. Neural Collaborative Filtering. In International Conference on World Wide Web."},{"key":"e_1_3_2_2_12_1","volume-title":"Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition.","author":"Huang Shanshan","year":"2025","unstructured":"Shanshan Huang, Haoxuan Li, Chunyuan Zheng, Mingyuan Ge, Wei Gao, Lei Wang, and Li Liu. 2025 a. Text-Driven Fashion Image Editing with Compositional Concept Learning and Counterfactual Abduction. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition."},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52734.2025.02187"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(98)00140-3"},{"key":"e_1_3_2_2_15_1","unstructured":"Adri\u00e1n Javaloy Pablo S\u00e1nchez-Mart\u00edn and Isabel Valera. 2024. Causal Normalizing Flows: From Theory to Practice. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2024.106173"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_18_1","volume-title":"Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random. In International World Wide Web Conference.","author":"Kweon Wonbin","year":"2024","unstructured":"Wonbin Kweon and Hwanjo Yu. 2024. Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random. In International World Wide Web Conference."},{"key":"e_1_3_2_2_19_1","volume-title":"FTS: A Framework to Find a Faithful TimeSieve. arXiv preprint arXiv:2405.19647(2024).","author":"Lai Songning","year":"2024","unstructured":"Songning Lai, Ninghui Feng, Haochen Sui, Ze Ma, Hao Wang, Zichen Song, Hang Zhao, and Yutao Yue. 2024. FTS: A Framework to Find a Faithful TimeSieve. arXiv preprint arXiv:2405.19647(2024)."},{"key":"e_1_3_2_2_20_1","volume-title":"TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. In International Conference on Learning Representations.","author":"Li Haoxuan","year":"2023","unstructured":"Haoxuan Li, Yan Lyu, Chunyuan Zheng, and Peng Wu. 2023a. TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_21_1","unstructured":"Haoxuan Li Kunhan Wu Chunyuan Zheng Yanghao Xiao Hao Wang Zhi Geng Fuli Feng Xiangnan He and Peng Wu. 2023b. Removing Hidden Confounding in Recommendation: A Unified Multi-Task Learning Approach. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583495"},{"key":"e_1_3_2_2_23_1","volume-title":"Propensity Matters: Measuring and Enhancing Balancing for Recommendation. In International Conference on Machine Learning.","author":"Li Haoxuan","year":"2023","unstructured":"Haoxuan Li, Yanghao Xiao, Chunyuan Zheng, Peng Wu, and Peng Cui. 2023d. Propensity Matters: Measuring and Enhancing Balancing for Recommendation. In International Conference on Machine Learning."},{"key":"e_1_3_2_2_24_1","volume-title":"International Conference on Learning Representations.","author":"Li Haoxuan","year":"2023","unstructured":"Haoxuan Li, Chunyuan Zheng, and Peng Wu. 2023 e. StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_25_1","volume-title":"Debiased Collaborative Filtering with Kernel-based Causal Balancing. In International Conference on Learning Representations.","author":"Li Haoxuan","year":"2024","unstructured":"Haoxuan Li, Chunyuan Zheng, Yanghao Xiao, Peng Wu, Zhi Geng, Xu Chen, and Peng Cui. 2024. Debiased Collaborative Filtering with Kernel-based Causal Balancing. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_26_1","volume-title":"AAAI Workshop on Artificial Intelligence with Causal Techniques.","author":"Li Meng","year":"2025","unstructured":"Meng Li and Haochen Sui. 2025. Causal Recommendation via Machine Unlearning with a Few Unbiased Data. In AAAI Workshop on Artificial Intelligence with Causal Techniques."},{"key":"e_1_3_2_2_27_1","volume-title":"KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data","author":"Liu Dugang","year":"2022","unstructured":"Dugang Liu, Pengxiang Cheng, Zinan Lin, Jinwei Luo, Zhenhua Dong, Xiuqiang He, Weike Pan, and Zhong Ming. 2022. KDCRec: Knowledge Distillation for Counterfactual Recommendation via Uniform Data. IEEE Transactions on Knowledge and Data Engineering(2022)."},{"key":"e_1_3_2_2_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460231.3474263"},{"key":"e_1_3_2_2_29_1","volume-title":"User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation. In International World Wide Web Conference.","author":"Liu Weiming","year":"2024","unstructured":"Weiming Liu, Chaochao Chen, Xinting Liao, Mengling Hu, Jiajie Su, Yanchao Tan, and Fan Wang. 2024. User Distribution Mapping Modelling with Collaborative Filtering for Cross Domain Recommendation. In International World Wide Web Conference."},{"key":"e_1_3_2_2_30_1","first-page":"3508","article-title":"Unbiased Recommendation Model Based on Improved Propensity Score Estimation","volume":"41","author":"Luo Jinwei","year":"2021","unstructured":"Jinwei Luo, Dugang Liu, Weike Pan, and Zhong Ming. 2021. Unbiased Recommendation Model Based on Improved Propensity Score Estimation. Journal of Computer Applications, Vol. 41, 12 (2021), 3508.","journal-title":"Journal of Computer Applications"},{"key":"e_1_3_2_2_31_1","volume-title":"Learning Causal Effects on Hypergraphs. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining.","author":"Ma Jing","year":"2022","unstructured":"Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent Hecht, and Jaime Teevan. 2022. Learning Causal Effects on Hypergraphs. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining."},{"key":"e_1_3_2_2_32_1","volume-title":"Collaborative Prediction and Ranking with Non-random Missing Data. In ACM Conference on Recommender Systems.","author":"Marlin Benjamin M","year":"2009","unstructured":"Benjamin M Marlin and Richard S Zemel. 2009. Collaborative Prediction and Ranking with Non-random Missing Data. In ACM Conference on Recommender Systems."},{"key":"e_1_3_2_2_33_1","first-page":"1","article-title":"Normalizing Flows for Probabilistic Modeling and Inference","volume":"22","author":"Papamakarios George","year":"2021","unstructured":"George Papamakarios, Eric Nalisnick, Danilo Jimenez Rezende, Shakir Mohamed, and Balaji Lakshminarayanan. 2021. Normalizing Flows for Probabilistic Modeling and Inference. Journal of Machine Learning Research, Vol. 22, 57 (2021), 1-64.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_34_1","unstructured":"Judea Pearl. 2009. Causality. Cambridge university press."},{"key":"e_1_3_2_2_35_1","volume-title":"Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback. In International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Saito Yuta","year":"2020","unstructured":"Yuta Saito. 2020. Asymmetric Tri-training for Debiasing Missing-Not-At-Random Explicit Feedback. In International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_36_1","volume-title":"Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions. In ACM Conference on Recommender Systems.","author":"Saito Yuta","year":"2020","unstructured":"Yuta Saito. 2020. Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions. In ACM Conference on Recommender Systems."},{"key":"e_1_3_2_2_37_1","volume-title":"Towards Resolving Propensity Contradiction in Offline Recommender Learning. In International Joint Conference on Artificial Intelligence.","author":"Saito Yuta","year":"2022","unstructured":"Yuta Saito and Masahiro Nomura. 2022. Towards Resolving Propensity Contradiction in Offline Recommender Learning. In International Joint Conference on Artificial Intelligence."},{"key":"e_1_3_2_2_38_1","volume-title":"International Conference on Machine Learning.","author":"Schnabel Tobias","year":"2016","unstructured":"Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims. 2016. Recommendations as Treatments: Debiasing Learning and Evaluation. In International Conference on Machine Learning."},{"key":"e_1_3_2_2_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835895"},{"key":"e_1_3_2_2_40_1","volume-title":"CE-RCFR: Robust Counterfactual Regression for Consensus-Enabled Treatment Effect Estimation. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining.","author":"Wang Fan","year":"2024","unstructured":"Fan Wang, Chaochao Chen, Weiming Liu, Tianhao Fan, Xinting Liao, Yanchao Tan, Lianyong Qi, and Xiaolin Zheng. 2024a. CE-RCFR: Robust Counterfactual Regression for Consensus-Enabled Treatment Effect Estimation. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining."},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"crossref","unstructured":"Fan Wang Lianyong Qi Weiming Liu Bowen Yu Jintao Chen and Yanwei Xu. 2025 c. Inter- and Intra- Similarity Preserved Counterfactual Incentive Effect Estimation for Recommendation Systems. ACM Transactions on Information Systems(2025).","DOI":"10.1145\/3722104"},{"key":"e_1_3_2_2_42_1","volume-title":"Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting. In AAAI Conference on Artificial Intelligence.","author":"Wang Hao","year":"2024","unstructured":"Hao Wang. 2024. Improving Neural Network Generalization on Data-Limited Regression with Doubly-Robust Boosting. In AAAI Conference on Artificial Intelligence."},{"key":"e_1_3_2_2_43_1","volume-title":"International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Wang Hao","year":"2022","unstructured":"Hao Wang, Tai-Wei Chang, Tianqiao Liu, Jianmin Huang, Zhichao Chen, Chao Yu, Ruopeng Li, and Wei Chu. 2022. ESCM^2: Entire Space Counterfactual Multi-task Model for Post-Click Conversion Rate Estimation. In International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_44_1","volume-title":"Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining.","author":"Wang Hao","year":"2025","unstructured":"Hao Wang, Zhichao Chen, Zhaoran Liu, Xu Chen, Haoxuan Li, and Zhouchen Lin. 2025 a. Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation. In ACM SIGKDD Conference on Knowledge Discovery and Data Mining."},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2024.3516584"},{"key":"e_1_3_2_2_46_1","unstructured":"Hao Wang Jiajun Fan Zhichao Chen Haoxuan Li Weiming Liu Tianqiao Liu Quanyu Dai Yichao Wang Zhenhua Dong and Ruiming Tang. 2023a. Optimal Transport for Treatment Effect Estimation. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_47_1","volume-title":"Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. In International Conference on Learning Representations.","author":"Wang Haotian","year":"2025","unstructured":"Haotian Wang, Haoxuan Li, Hao Zou, Haoang Chi, Long Lan, Wanrong Huang, and Wenjing Yang. 2025 b. Effective and Efficient Time-Varying Counterfactual Prediction with State-Space Models. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_48_1","volume-title":"Causal Recommendation: Progresses and Future Directions. In International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Wang Wenjie","year":"2023","unstructured":"Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, and Xiangnan He. 2023b. Causal Recommendation: Progresses and Future Directions. In International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_49_1","volume-title":"International Conference on Machine Learning.","author":"Wang Xiaojie","year":"2019","unstructured":"Xiaojie Wang, Rui Zhang, Yu Sun, and Jianzhong Qi. 2019. Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random. In International Conference on Machine Learning."},{"key":"e_1_3_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3437963.3441799"},{"key":"e_1_3_2_2_51_1","unstructured":"Zifeng Wang Xi Chen Rui Wen Shao-Lun Huang Ercan Kuruoglu and Yefeng Zheng. 2020. Information Theoretic Counterfactual Learning from Missing-Not-at-Random Feedback. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_52_1","unstructured":"Peng Wu Haoxuan Li Yuhao Deng Wenjie Hu Quanyu Dai Zhenhua Dong Jie Sun Rui Zhang and Xiao-Hua Zhou. 2022. On the Opportunity of Causal Learning in Recommendation Systems: Foundation Estimation Prediction and Challenges. arXiv preprint arXiv:2201.06716(2022)."},{"key":"e_1_3_2_2_53_1","volume-title":"Invariant Spatiotemporal Representation Learning for Cross-patient Seizure Classification. In NeurIPS Workshop on NeuroAI.","author":"Wu Yuntian","year":"2024","unstructured":"Yuntian Wu, Yuntian Yang, Jiabao Sean Xiao, Chuan Zhou, Haochen Sui, and Haoxuan Li. 2024. Invariant Spatiotemporal Representation Learning for Cross-patient Seizure Classification. In NeurIPS Workshop on NeuroAI."},{"key":"e_1_3_2_2_54_1","volume-title":"Indeterminacy in Generative Models: Characterization and Strong Identifiability. In International Conference on Artificial Intelligence and Statistics.","author":"Xi Quanhan","year":"2023","unstructured":"Quanhan Xi and Benjamin Bloem-Reddy. 2023. Indeterminacy in Generative Models: Characterization and Strong Identifiability. In International Conference on Artificial Intelligence and Statistics."},{"key":"e_1_3_2_2_55_1","unstructured":"Yanghao Xiao Haoxuan Li Yongqiang Tang and Wensheng Zhang. 2024. Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation. In Advances in Neural Information Processing Systems."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380037"},{"key":"e_1_3_2_2_57_1","volume-title":"Adaptive Structure Learning with Partial Parameter Sharing for Post-Click Conversion Rate Prediction. In International ACM SIGIR Conference on Research and Development in Information Retrieval.","author":"Zheng Chunyuan","year":"2025","unstructured":"Chunyuan Zheng, Hang Pan, Yang Zhang, and Haoxuan Li. 2025. Adaptive Structure Learning with Partial Parameter Sharing for Post-Click Conversion Rate Prediction. In International ACM SIGIR Conference on Research and Development in Information Retrieval."},{"key":"e_1_3_2_2_58_1","doi-asserted-by":"publisher","DOI":"10.1145\/3690624.3709161"}],"event":{"name":"KDD '25: The 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Toronto ON Canada","acronym":"KDD '25","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3711896.3736832","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,16]],"date-time":"2025-08-16T14:32:19Z","timestamp":1755354739000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3711896.3736832"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,3]]},"references-count":58,"alternative-id":["10.1145\/3711896.3736832","10.1145\/3711896"],"URL":"https:\/\/doi.org\/10.1145\/3711896.3736832","relation":{},"subject":[],"published":{"date-parts":[[2025,8,3]]},"assertion":[{"value":"2025-08-03","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}