{"total":13,"rows":[{"id":"2406.01285","title":"Large Language Models as Recommender Systems: A Study of Popularity Bias","created":"2024-06-03","cited_by_count":26,"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":"2309.01610","title":"Fairness in Ranking under Disparate Uncertainty","created":"2023-09-04","cited_by_count":4,"area":null},{"id":"2405.09543","title":"Algorithmic Fairness: A Tolerance Perspective","created":"2024-04-26","cited_by_count":2,"area":null},{"id":"2408.09168","title":"Ranking Across Different Content Types: The Robust Beauty of Multinomial Blending","created":"2024-08-17","cited_by_count":2,"area":null},{"id":"2406.10262","title":"Fast solution to the fair ranking problem using the Sinkhorn algorithm","created":"2024-06-11","cited_by_count":1,"area":null},{"id":"2502.11429","title":"What's in a Query: Polarity-Aware Distribution-Based Fair Ranking","created":"2025-02-17","cited_by_count":1,"area":null},{"id":"2509.09037","title":"Envy-Free but Still Unfair: Envy-Freeness Up To One Item (EF-1) in Personalized Recommendation","created":"2025-09-10","cited_by_count":1,"area":null},{"id":"2509.24077","title":"Demographic-Agnostic Fairness without Harm","created":"2025-09-28","cited_by_count":1,"area":null},{"id":"2307.10204","title":"An IPW-based Unbiased Ranking Metric in Two-sided Markets","created":"2023-07-14","cited_by_count":0,"area":null},{"id":"2405.01711","title":"Individual Fairness Through Reweighting and Tuning","created":"2024-05-02","cited_by_count":0,"area":null},{"id":"2602.15752","title":"Beyond Match Maximization and Fairness: Retention-Optimized Two-Sided Matching","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2606.26369","title":"Scoring Is Not Enough: Addressing Gaps in Utility-fairness Trade-offs for Ranking","created":"2026-06-24","cited_by_count":0,"area":null}],"next_cursor":null}