{"total":45,"rows":[{"id":"2309.00770","title":"Bias and Fairness in Large Language Models: A Survey","created":"2023-09-02","cited_by_count":639,"area":null},{"id":"2308.10149","title":"A Survey on Fairness in Large Language Models","created":"2023-08-20","cited_by_count":95,"area":null},{"id":"2109.08253","title":"Balancing out Bias: Achieving Fairness Through Balanced Training","created":"2021-09-16","cited_by_count":34,"area":null},{"id":"2109.10645","title":"Contrastive Learning for Fair Representations","created":"2021-09-22","cited_by_count":34,"area":null},{"id":"2203.07893","title":"Gold Doesn't Always Glitter: Spectral Removal of Linear and Nonlinear Guarded Attribute Information","created":"2022-03-15","cited_by_count":34,"area":null},{"id":"2210.14975","title":"MABEL: Attenuating Gender Bias using Textual Entailment Data","created":"2022-10-26","cited_by_count":31,"area":null},{"id":"2109.10441","title":"Evaluating Debiasing Techniques for Intersectional Biases","created":"2021-09-21","cited_by_count":30,"area":null},{"id":"2306.08158","title":"Sociodemographic Bias in Language Models: A Survey and Forward Path","created":"2023-06-13","cited_by_count":28,"area":null},{"id":"2302.06321","title":"Parameter-efficient Modularised Bias Mitigation via AdapterFusion","created":"2023-02-13","cited_by_count":25,"area":null},{"id":"2406.05392","title":"Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey","created":"2024-06-08","cited_by_count":23,"area":null},{"id":"2205.02393","title":"Optimising Equal Opportunity Fairness in Model Training","created":"2022-05-05","cited_by_count":22,"area":null},{"id":"2212.10563","title":"BLIND: Bias Removal With No Demographics","created":"2022-12-20","cited_by_count":22,"area":null},{"id":"2307.01595","title":"Prompt Tuning Pushes Farther, Contrastive Learning Pulls Closer: A Two-Stage Approach to Mitigate Social Biases","created":"2023-07-04","cited_by_count":21,"area":null},{"id":"2109.10444","title":"Fairness-aware Class Imbalanced Learning","created":"2021-09-21","cited_by_count":19,"area":null},{"id":"2205.15171","title":"Modular and On-demand Bias Mitigation with Attribute-Removal Subnetworks","created":"2022-05-30","cited_by_count":18,"area":null},{"id":"2405.09341","title":"Large Language Model Bias Mitigation from the Perspective of Knowledge Editing","created":"2024-05-15","cited_by_count":16,"area":null},{"id":"2310.12490","title":"Co$^2$PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning","created":"2023-10-19","cited_by_count":15,"area":null},{"id":"2408.11843","title":"Identifying and Mitigating Social Bias Knowledge in Language Models","created":"2024-08-07","cited_by_count":13,"area":null},{"id":"2402.12193","title":"A Chinese Dataset for Evaluating the Safeguards in Large Language Models","created":"2024-02-19","cited_by_count":12,"area":null},{"id":"2205.11485","title":"Conditional Supervised Contrastive Learning for Fair Text Classification","created":"2022-05-23","cited_by_count":11,"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":"2312.01509","title":"Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societies","created":"2023-12-03","cited_by_count":11,"area":null},{"id":"2205.06135","title":"Fair NLP Models with Differentially Private Text Encoders","created":"2022-05-12","cited_by_count":9,"area":null},{"id":"2311.07115","title":"Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions","created":"2023-11-13","cited_by_count":9,"area":null},{"id":"2203.06317","title":"Towards Equal Opportunity Fairness through Adversarial Learning","created":"2022-03-12","cited_by_count":8,"area":null},{"id":"2206.10923","title":"FairGrad: Fairness Aware Gradient Descent","created":"2022-06-22","cited_by_count":8,"area":null},{"id":"2401.16457","title":"Effective Controllable Bias Mitigation for Classification and Retrieval using Gate Adapters","created":"2024-01-29","cited_by_count":8,"area":null},{"id":"2303.08403","title":"DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision","created":"2023-03-15","cited_by_count":6,"area":null},{"id":"2505.14449","title":"Mitigating Subgroup Disparities in Multi-Label Speech Emotion Recognition: A Pseudo-Labeling and Unsupervised Learning Approach","created":"2025-05-20","cited_by_count":5,"area":null},{"id":"2205.01876","title":"fairlib: A Unified Framework for Assessing and Improving Classification Fairness","created":"2022-05-04","cited_by_count":4,"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":"2506.04652","title":"EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition","created":"2025-06-05","cited_by_count":3,"area":null},{"id":"2310.15114","title":"How To Build Competitive Multi-gender Speech Translation Models For Controlling Speaker Gender Translation","created":"2023-10-23","cited_by_count":2,"area":null},{"id":"2410.04472","title":"Collapsed Language Models Promote Fairness","created":"2024-10-06","cited_by_count":1,"area":null},{"id":"2305.12671","title":"Transferring Fairness using Multi-Task Learning with Limited Demographic Information","created":"2023-05-22","cited_by_count":0,"area":null},{"id":"2406.04876","title":"HateDebias: On the Diversity and Variability of Hate Speech Debiasing","created":"2024-06-07","cited_by_count":0,"area":null},{"id":"2407.19345","title":"Inference-Time Selective Debiasing to Enhance Fairness in Text Classification Models","created":"2024-07-27","cited_by_count":0,"area":null},{"id":"2504.01030","title":"Fair Sufficient Representation Learning","created":"2025-03-29","cited_by_count":0,"area":null},{"id":"2504.06470","title":"Deep Fair Learning: Task-Aware Fair Representations via Joint Distance-Covariance Regularization","created":"2025-04-08","cited_by_count":0,"area":null},{"id":"2508.11258","title":"Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing","created":"2025-08-15","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}],"next_cursor":null}