{"total":22,"rows":[{"id":"2205.11127","title":"Fairness in Recommender Systems: Research Landscape and Future Directions","created":"2022-05-23","cited_by_count":30,"area":null},{"id":"2107.06720","title":"Fairness in Ranking under Uncertainty","created":"2021-07-14","cited_by_count":27,"area":null},{"id":"2201.12662","title":"Fair ranking: a critical review, challenges, and future directions","created":"2022-01-29","cited_by_count":21,"area":null},{"id":"2211.17067","title":"Fair Ranking with Noisy Protected Attributes","created":"2022-11-30","cited_by_count":17,"area":null},{"id":"2204.13568","title":"Justice in Misinformation Detection Systems: An Analysis of Algorithms, Stakeholders, and Potential Harms","created":"2022-04-28","cited_by_count":10,"area":null},{"id":"2109.08549","title":"Measuring Fairness Under Unawareness of Sensitive Attributes: A Quantification-Based Approach","created":"2021-09-17","cited_by_count":9,"area":null},{"id":"2304.11123","title":"China and the U.S. produce more impactful AI research when collaborating together","created":"2023-04-21","cited_by_count":6,"area":null},{"id":"2305.19407","title":"FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection","created":"2023-05-30","cited_by_count":6,"area":null},{"id":"2307.03306","title":"When Fair Classification Meets Noisy Protected Attributes","created":"2023-07-06","cited_by_count":6,"area":null},{"id":"2406.04298","title":"Measuring and Addressing Indexical Bias in Information Retrieval","created":"2024-06-06","cited_by_count":6,"area":null},{"id":"2205.02414","title":"Subverting Fair Image Search with Generative Adversarial Perturbations","created":"2022-05-05","cited_by_count":5,"area":null},{"id":"2302.03810","title":"Fairness in Matching under Uncertainty","created":"2023-02-08","cited_by_count":5,"area":null},{"id":"2403.05975","title":"Measuring Bias in a Ranked List using Term-based Representations","created":"2024-03-09","cited_by_count":4,"area":null},{"id":"2405.16762","title":"Addressing Discretization-Induced Bias in Demographic Prediction","created":"2024-05-27","cited_by_count":4,"area":null},{"id":"2305.05608","title":"The Role of Relevance in Fair Ranking","created":"2023-05-09","cited_by_count":3,"area":null},{"id":"2502.17921","title":"Unmasking Gender Bias in Recommendation Systems and Enhancing Category-Aware Fairness","created":"2025-02-25","cited_by_count":3,"area":null},{"id":"2212.14351","title":"Properties of Group Fairness Metrics for Rankings","created":"2022-12-29","cited_by_count":2,"area":null},{"id":"2306.11964","title":"Sampling Individually-Fair Rankings that are Always Group Fair","created":"2023-06-21","cited_by_count":2,"area":null},{"id":"2407.17459","title":"Hidden or Inferred: Fair Learning-To-Rank with Unknown Demographics","created":"2024-07-24","cited_by_count":2,"area":null},{"id":"2111.00735","title":"Calibrating Explore-Exploit Trade-off for Fair Online Learning to Rank","created":"2021-11-01","cited_by_count":1,"area":null},{"id":"2502.05333","title":"A Tutorial On Intersectionality in Fair Rankings","created":"2025-02-07","cited_by_count":0,"area":null},{"id":"2608.09899","title":"Fairness in Link Prediction Beyond Demographic Parity: A Reproducibility Study","created":"2026-08-10","cited_by_count":0,"area":null}],"next_cursor":null}