{"total":16,"rows":[{"id":"2310.18286","title":"Optimal Transport for Treatment Effect Estimation","created":"2023-10-27","cited_by_count":32,"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":"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":"2407.01111","title":"Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation","created":"2024-07-01","cited_by_count":7,"area":null},{"id":"2404.19596","title":"Debiased Collaborative Filtering with Kernel-Based Causal Balancing","created":"2024-04-30","cited_by_count":6,"area":null},{"id":"2404.19644","title":"MetaCoCo: A New Few-Shot Classification Benchmark with Spurious Correlation","created":"2024-04-30","cited_by_count":5,"area":null},{"id":"2308.02925","title":"ConvFormer: Revisiting Transformer for Sequential User Modeling","created":"2023-08-05","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":"2404.19620","title":"Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference","created":"2024-04-30","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":"2501.08067","title":"Optimal Policy Adaptation under Covariate Shift","created":"2025-01-14","cited_by_count":0,"area":null},{"id":"2501.08888","title":"A Partial Initialization Strategy to Mitigate the Overfitting Problem in CATE Estimation with Hidden Confounding","created":"2025-01-15","cited_by_count":0,"area":null},{"id":"2506.07517","title":"Addressing Correlated Latent Exogenous Variables in Debiased Recommender Systems","created":"2025-06-09","cited_by_count":0,"area":null},{"id":"2605.21066","title":"PUID: A Personalized Deconfounding Framework for Recommender Systems under Hidden Confounding","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2606.21911","title":"The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders","created":"2026-06-20","cited_by_count":0,"area":null}],"next_cursor":null}