{"total":72,"rows":[{"id":"2105.13623","title":"Enhanced Doubly Robust Learning for Debiasing Post-click Conversion Rate Estimation","created":"2021-05-28","cited_by_count":28,"area":null},{"id":"2205.13619","title":"Fairness in Recommendation: Foundations, Methods and Applications","created":"2022-05-26","cited_by_count":27,"area":null},{"id":"2205.04701","title":"StableDR: Stabilized Doubly Robust Learning for Recommendation on Data Missing Not at Random","created":"2022-05-10","cited_by_count":24,"area":null},{"id":"2109.02444","title":"Top-N Recommendation with Counterfactual User Preference Simulation","created":"2021-09-02","cited_by_count":21,"area":null},{"id":"2404.12008","title":"How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective","created":"2024-04-18","cited_by_count":21,"area":null},{"id":"2203.10258","title":"TDR-CL: Targeted Doubly Robust Collaborative Learning for Debiased Recommendations","created":"2022-03-19","cited_by_count":18,"area":null},{"id":"2211.06684","title":"A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction","created":"2022-11-12","cited_by_count":18,"area":null},{"id":"2304.09085","title":"Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations","created":"2023-04-17","cited_by_count":18,"area":null},{"id":"2202.03984","title":"CausPref: Causal Preference Learning for Out-of-Distribution Recommendation","created":"2022-02-08","cited_by_count":17,"area":null},{"id":"2110.07122","title":"Deconfounded Causal Collaborative Filtering","created":"2021-10-14","cited_by_count":14,"area":null},{"id":"2207.01616","title":"Breaking Feedback Loops in Recommender Systems with Causal Inference","created":"2022-07-04","cited_by_count":14,"area":null},{"id":"2102.01868","title":"Causal Collaborative Filtering","created":"2021-02-03","cited_by_count":13,"area":null},{"id":"2202.02576","title":"Causal Disentanglement for Semantics-Aware Intent Learning in Recommendation","created":"2022-02-05","cited_by_count":12,"area":null},{"id":"2310.10696","title":"Robust Collaborative Filtering to Popularity Distribution Shift","created":"2023-10-16","cited_by_count":12,"area":null},{"id":"2207.10796","title":"Multiple Robust Learning for Recommendation","created":"2022-07-09","cited_by_count":11,"area":null},{"id":"2306.03527","title":"Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao","created":"2023-06-06","cited_by_count":11,"area":null},{"id":"2102.13302","title":"Variation Control and Evaluation for Generative SlateRecommendations","created":"2021-02-26","cited_by_count":10,"area":null},{"id":"2209.08860","title":"A Survey of Deep Causal Models and Their Industrial Applications","created":"2022-09-19","cited_by_count":10,"area":null},{"id":"2105.07775","title":"Be Causal: De-biasing Social Network Confounding in Recommendation","created":"2021-05-17","cited_by_count":9,"area":null},{"id":"2212.11431","title":"Local Policy Improvement for Recommender Systems","created":"2022-12-22","cited_by_count":9,"area":null},{"id":"2109.09587","title":"Recommender systems based on graph embedding techniques: A comprehensive review","created":"2021-09-20","cited_by_count":8,"area":null},{"id":"2204.12176","title":"Cross Pairwise Ranking for Unbiased Item Recommendation","created":"2022-04-26","cited_by_count":8,"area":null},{"id":"2406.17182","title":"Debiased Recommendation with Noisy Feedback","created":"2024-06-24","cited_by_count":8,"area":null},{"id":"2403.00817","title":"Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random","created":"2024-02-26","cited_by_count":7,"area":null},{"id":"2502.13840","title":"Unbiased Collaborative Filtering with Fair Sampling","created":"2025-02-19","cited_by_count":6,"area":null},{"id":"2109.06037","title":"Correcting the User Feedback-Loop Bias for Recommendation Systems","created":"2021-09-13","cited_by_count":5,"area":null},{"id":"2206.00416","title":"In the Eye of the Beholder: Robust Prediction with Causal User Modeling","created":"2022-06-01","cited_by_count":5,"area":null},{"id":"2206.00568","title":"RMT-Net: Reject-aware Multi-Task Network for Modeling Missing-not-at-random Data in Financial Credit Scoring","created":"2022-06-01","cited_by_count":5,"area":null},{"id":"2302.01198","title":"Causal Lifting and Link Prediction","created":"2023-02-02","cited_by_count":5,"area":null},{"id":"2408.09748","title":"Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method","created":"2024-08-19","cited_by_count":5,"area":null},{"id":"2108.12100","title":"A framework for massive scale personalized promotion","created":"2021-08-27","cited_by_count":4,"area":null},{"id":"2112.10274","title":"Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies","created":"2021-12-19","cited_by_count":4,"area":null},{"id":"2112.15434","title":"Adversarial Learning for Incentive Optimization in Mobile Payment Marketing","created":"2021-12-28","cited_by_count":4,"area":null},{"id":"2204.07221","title":"Causal Disentanglement with Network Information for Debiased Recommendations","created":"2022-04-14","cited_by_count":4,"area":null},{"id":"2207.12660","title":"Bilateral Self-unbiased Learning from Biased Implicit Feedback","created":"2022-07-26","cited_by_count":3,"area":null},{"id":"2308.04706","title":"Pareto Invariant Representation Learning for Multimedia Recommendation","created":"2023-08-09","cited_by_count":3,"area":null},{"id":"2208.11094","title":"Dynamic Causal Collaborative Filtering","created":"2022-08-23","cited_by_count":2,"area":null},{"id":"2210.10256","title":"Causal Structure Learning with Recommendation System","created":"2022-10-19","cited_by_count":2,"area":null},{"id":"2303.12973","title":"Uncertainty Calibration for Counterfactual Propensity Estimation in Recommendation","created":"2023-03-23","cited_by_count":2,"area":null},{"id":"2305.14083","title":"Counterfactual Augmentation for Multimodal Learning Under Presentation Bias","created":"2023-05-23","cited_by_count":2,"area":null},{"id":"2403.03578","title":"Causal Disentanglement for Regulating Social Influence Bias in Social Recommendation","created":"2024-03-06","cited_by_count":2,"area":null},{"id":"2508.09334","title":"RicciFlowRec: A Geometric Root Cause Recommender Using Ricci Curvature on Financial Graphs","created":"2025-08-12","cited_by_count":2,"area":null},{"id":"2510.19517","title":"Bi-Level Decision-Focused Causal Learning for Large-Scale Marketing Optimization: Bridging Observational and Experimental Data","created":"2025-10-22","cited_by_count":2,"area":null},{"id":"2605.27043","title":"Causal Representation Learning for Generalisable Recommendation","created":"2026-05-26","cited_by_count":2,"area":null},{"id":"2107.06630","title":"Online Evaluation Methods for the Causal Effect of Recommendations","created":"2021-07-14","cited_by_count":1,"area":null},{"id":"2112.01160","title":"Learning Robust Recommender from Noisy Implicit Feedback","created":"2021-12-02","cited_by_count":1,"area":null},{"id":"2112.05695","title":"Causal Knowledge Guided Societal Event Forecasting","created":"2021-12-10","cited_by_count":1,"area":null},{"id":"2201.04952","title":"REST: Debiased Social Recommendation via Reconstructing Exposure Strategies","created":"2022-01-13","cited_by_count":1,"area":null},{"id":"2305.15431","title":"Exploring and Exploiting Data Heterogeneity in Recommendation","created":"2023-05-21","cited_by_count":1,"area":null},{"id":"2309.15418","title":"Automatic Feature Fairness in Recommendation via Adversaries","created":"2023-09-27","cited_by_count":1,"area":null},{"id":"2407.14094","title":"User-Creator Feature Polarization in Recommender Systems with Dual Influence","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2408.09646","title":"Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems","created":"2024-08-19","cited_by_count":1,"area":null},{"id":"2408.09651","title":"Interaction-Data-guided Conditional Instrumental Variables for Debiasing Recommender Systems","created":"2024-08-19","cited_by_count":1,"area":null},{"id":"2410.01822","title":"The Importance of Causality in Decision Making: A Perspective on Recommender Systems","created":"2024-09-16","cited_by_count":1,"area":null},{"id":"2505.17717","title":"A Distributionally Robust Framework for Nuisance in Causal Effect Estimation","created":"2025-05-23","cited_by_count":1,"area":null},{"id":"2511.14768","title":"Causally-Informed Reinforcement Learning for Adaptive Emotion-Aware Social Media Recommendation","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2512.10688","title":"Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decomposition","created":"2025-12-11","cited_by_count":1,"area":null},{"id":"2603.25126","title":"MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2112.00591","title":"AI Assurance using Causal Inference: Application to Public Policy","created":"2021-12-01","cited_by_count":0,"area":null},{"id":"2206.03851","title":"Reconsidering Learning Objectives in Unbiased Recommendation with Unobserved Confounders","created":"2022-06-07","cited_by_count":0,"area":null},{"id":"2310.04855","title":"Epsilon non-Greedy: A Bandit Approach for Unbiased Recommendation via Uniform Data","created":"2023-10-07","cited_by_count":0,"area":null},{"id":"2310.15772","title":"Analyzing User Characteristics of Hate Speech Spreaders on Social Media","created":"2023-10-24","cited_by_count":0,"area":null},{"id":"2311.03381","title":"Separating and Learning Latent Confounders to Enhancing User Preferences Modeling","created":"2023-11-02","cited_by_count":0,"area":null},{"id":"2311.05864","title":"DPR: An Algorithm Mitigate Bias Accumulation in Recommendation feedback loops","created":"2023-11-10","cited_by_count":0,"area":null},{"id":"2403.00798","title":"Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization","created":"2024-02-23","cited_by_count":0,"area":null},{"id":"2507.03271","title":"LILI clustering algorithm: Limit Inferior Leaf Interval Integrated into Causal Forest for Causal Interference","created":"2025-07-04","cited_by_count":0,"area":null},{"id":"2507.04722","title":"LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Recommender Systems","created":"2025-07-07","cited_by_count":0,"area":null},{"id":"2512.14733","title":"Where to Explore: A Reach and Cost-Aware Approach for Unbiased Data Collection in Recommender Systems","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2603.20338","title":"Low-pass Personalized Subgraph Federated Recommendation","created":"2026-03-20","cited_by_count":0,"area":null},{"id":"2605.11145","title":"Debiasing Message Passing to Mitigate Popularity Bias in GNN-based Collaborative Filtering","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2608.10182","title":"From Prediction to Incrementality: Causal Optimization for Large-Scale Targeting and Recommendation","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2609.02162","title":"GenCAR: Generative Counterfactual Alignment with Risk-Controlled Selection for Out-of-Distribution Recommendation","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}