{"total":21,"rows":[{"id":"2212.10563","title":"BLIND: Bias Removal With No Demographics","created":"2022-12-20","cited_by_count":22,"area":null},{"id":"2210.06732","title":"Equal Improvability: A New Fairness Notion Considering the Long-term Impact","created":"2022-10-13","cited_by_count":13,"area":null},{"id":"2302.05711","title":"Fair Enough: Standardizing Evaluation and Model Selection for Fairness Research in NLP","created":"2023-02-11","cited_by_count":11,"area":null},{"id":"2311.03714","title":"Loss Balancing for Fair Supervised Learning","created":"2023-11-07","cited_by_count":11,"area":null},{"id":"2302.07372","title":"Same Same, But Different: Conditional Multi-Task Learning for Demographic-Specific Toxicity Detection","created":"2023-02-14","cited_by_count":10,"area":null},{"id":"2305.06074","title":"iLab at SemEval-2023 Task 11 Le-Wi-Di: Modelling Disagreement or Modelling Perspectives?","created":"2023-05-10","cited_by_count":10,"area":null},{"id":"2311.12689","title":"Fair Text Classification with Wasserstein Independence","created":"2023-11-21","cited_by_count":4,"area":null},{"id":"2404.00463","title":"Addressing Both Statistical and Causal Gender Fairness in NLP Models","created":"2024-03-30","cited_by_count":4,"area":null},{"id":"2210.08758","title":"Systematic Evaluation of Predictive Fairness","created":"2022-10-17","cited_by_count":3,"area":null},{"id":"2503.07691","title":"Fair Text Classification via Transferable Representations","created":"2025-03-10","cited_by_count":3,"area":null},{"id":"2501.13219","title":"Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling","created":"2025-01-22","cited_by_count":2,"area":null},{"id":"2210.04369","title":"A Differentiable Distance Approximation for Fairer Image Classification","created":"2022-10-09","cited_by_count":1,"area":null},{"id":"2310.16517","title":"OccuQuest: Mitigating Occupational Bias for Inclusive Large Language Models","created":"2023-10-25","cited_by_count":1,"area":null},{"id":"2311.08472","title":"Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models","created":"2023-11-14","cited_by_count":1,"area":null},{"id":"2404.03833","title":"An ExplainableFair Framework for Prediction of Substance Use Disorder Treatment Completion","created":"2024-04-04","cited_by_count":1,"area":null},{"id":"2407.11933","title":"Fairness-Aware Multi-Group Target Detection in Online Discussion","created":"2024-07-16","cited_by_count":1,"area":null},{"id":"2410.01324","title":"Fair Class-Incremental Learning using Sample Weighting","created":"2024-10-02","cited_by_count":0,"area":null},{"id":"2411.10636","title":"Mitigating Extrinsic Gender Bias for Bangla Classification Tasks","created":"2024-11-16","cited_by_count":0,"area":null},{"id":"2509.06164","title":"Benchmarking Gender and Political Bias in Large Language Models","created":"2025-09-07","cited_by_count":0,"area":null},{"id":"2510.23935","title":"Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis","created":"2025-10-27","cited_by_count":0,"area":null},{"id":"2601.05352","title":"When the Server Steps In: Calibrated Updates for Fair Federated Learning","created":"2026-01-08","cited_by_count":0,"area":null}],"next_cursor":null}