{"total":97,"rows":[{"id":"2110.06733","title":"Systematic Inequalities in Language Technology Performance across the World's Languages","created":"2021-10-13","cited_by_count":120,"area":null},{"id":"2106.06054","title":"Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline","created":"2021-06-02","cited_by_count":49,"area":null},{"id":"2109.12072","title":"SD-QA: Spoken Dialectal Question Answering for the Real World","created":"2021-09-24","cited_by_count":38,"area":null},{"id":"2207.03277","title":"A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers","created":"2022-07-07","cited_by_count":30,"area":null},{"id":"2110.15781","title":"Two-sided fairness in rankings via Lorenz dominance","created":"2021-10-28","cited_by_count":28,"area":null},{"id":"2110.09253","title":"A Sociotechnical View of Algorithmic Fairness","created":"2021-09-27","cited_by_count":24,"area":null},{"id":"2112.03497","title":"Dataset Geography: Mapping Language Data to Language Users","created":"2021-12-07","cited_by_count":22,"area":null},{"id":"2212.06140","title":"Fairify: Fairness Verification of Neural Networks","created":"2022-12-08","cited_by_count":22,"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":"2205.05770","title":"De-biasing \"bias\" measurement","created":"2022-05-11","cited_by_count":20,"area":null},{"id":"2106.06797","title":"Machine Translation into Low-resource Language Varieties","created":"2021-06-12","cited_by_count":19,"area":null},{"id":"2505.21091","title":"Position is Power: System Prompts as a Mechanism of Bias in Large Language Models (LLMs)","created":"2025-05-27","cited_by_count":19,"area":null},{"id":"2104.14504","title":"An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning","created":"2021-04-29","cited_by_count":18,"area":null},{"id":"2105.04273","title":"Loss-Aversively Fair Classification","created":"2021-05-10","cited_by_count":18,"area":null},{"id":"2206.04101","title":"What-is and How-to for Fairness in Machine Learning: A Survey, Reflection, and Perspective","created":"2022-06-08","cited_by_count":18,"area":null},{"id":"2212.04593","title":"Towards Understanding Fairness and its Composition in Ensemble Machine Learning","created":"2022-12-08","cited_by_count":17,"area":null},{"id":"2304.03646","title":"Fairness through Aleatoric Uncertainty","created":"2023-04-07","cited_by_count":16,"area":null},{"id":"2205.13421","title":"Bias in Machine Learning Models Can Be Significantly Mitigated by Careful Training: Evidence from Neuroimaging Studies","created":"2022-05-26","cited_by_count":14,"area":null},{"id":"2204.06521","title":"Optimizing generalized Gini indices for fairness in rankings","created":"2022-04-02","cited_by_count":13,"area":null},{"id":"2211.07907","title":"MMD-B-Fair: Learning Fair Representations with Statistical Testing","created":"2022-11-15","cited_by_count":13,"area":null},{"id":"2103.13868","title":"Equality before the Law: Legal Judgment Consistency Analysis for Fairness","created":"2021-03-25","cited_by_count":11,"area":null},{"id":"2207.06084","title":"Towards A Holistic View of Bias in Machine Learning: Bridging Algorithmic Fairness and Imbalanced Learning","created":"2022-07-13","cited_by_count":10,"area":null},{"id":"2407.06235","title":"Auditing of AI: Legal, Ethical and Technical Approaches","created":"2024-07-07","cited_by_count":10,"area":null},{"id":"2205.15935","title":"Bias-inducing geometries: an exactly solvable data model with fairness implications","created":"2022-05-31","cited_by_count":9,"area":null},{"id":"2302.04118","title":"On the Richness of Calibration","created":"2023-02-08","cited_by_count":9,"area":null},{"id":"2306.09995","title":"Fairness in Preference-based Reinforcement Learning","created":"2023-06-16","cited_by_count":9,"area":null},{"id":"2406.08819","title":"AIM: Attributing, Interpreting, Mitigating Data Unfairness","created":"2024-06-13","cited_by_count":9,"area":null},{"id":"2202.01615","title":"Measuring Disparate Outcomes of Content Recommendation Algorithms with Distributional Inequality Metrics","created":"2022-02-03","cited_by_count":8,"area":null},{"id":"2210.16754","title":"Mitigating Unfairness via Evolutionary Multi-objective Ensemble Learning","created":"2022-10-30","cited_by_count":8,"area":null},{"id":"2207.06273","title":"Understanding Unfairness in Fraud Detection through Model and Data Bias Interactions","created":"2022-07-13","cited_by_count":7,"area":null},{"id":"2108.02662","title":"Reducing Unintended Bias of ML Models on Tabular and Textual Data","created":"2021-08-05","cited_by_count":6,"area":null},{"id":"2305.13057","title":"Causality-Aided Trade-off Analysis for Machine Learning Fairness","created":"2023-05-22","cited_by_count":6,"area":null},{"id":"2203.08670","title":"Measuring Fairness of Text Classifiers via Prediction Sensitivity","created":"2022-03-16","cited_by_count":5,"area":null},{"id":"2209.07912","title":"Algorithmic decision making methods for fair credit scoring","created":"2022-09-16","cited_by_count":5,"area":null},{"id":"2212.06750","title":"FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data","created":"2022-12-13","cited_by_count":5,"area":null},{"id":"2306.00183","title":"Diffused Redundancy in Pre-trained Representations","created":"2023-05-31","cited_by_count":5,"area":"mechinterp"},{"id":"2311.06826","title":"Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms","created":"2023-11-12","cited_by_count":5,"area":null},{"id":"2207.12138","title":"Towards Fairness-Aware Multi-Objective Optimization","created":"2022-07-22","cited_by_count":4,"area":null},{"id":"2404.01877","title":"Procedural Fairness in Machine Learning","created":"2024-04-02","cited_by_count":4,"area":null},{"id":"2408.06509","title":"Fooling SHAP with Output Shuffling Attacks","created":"2024-08-12","cited_by_count":4,"area":null},{"id":"2508.15193","title":"Revisiting Pre-processing Group Fairness: A Modular Benchmarking Framework","created":"2025-08-21","cited_by_count":4,"area":null},{"id":"2102.00753","title":"Quantum Fair Machine Learning","created":"2021-02-01","cited_by_count":3,"area":null},{"id":"2106.02702","title":"Subgroup Fairness in Two-Sided Markets","created":"2021-06-04","cited_by_count":3,"area":null},{"id":"2206.02897","title":"Distributive Justice as the Foundational Premise of Fair ML: Unification, Extension, and Interpretation of Group Fairness Metrics","created":"2022-06-06","cited_by_count":3,"area":null},{"id":"2304.04029","title":"Bipol: A Novel Multi-Axes Bias Evaluation Metric with Explainability for NLP","created":"2023-04-08","cited_by_count":3,"area":null},{"id":"2310.08455","title":"Metrics for popularity bias in dynamic recommender systems","created":"2023-10-12","cited_by_count":3,"area":null},{"id":"2312.08064","title":"Human-in-the-loop Fairness: Integrating Stakeholder Feedback to Incorporate Fairness Perspectives in Responsible AI","created":"2023-12-13","cited_by_count":3,"area":null},{"id":"2401.00093","title":"Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing System","created":"2023-12-29","cited_by_count":3,"area":null},{"id":"2409.12428","title":"Is it Still Fair? A Comparative Evaluation of Fairness Algorithms through the Lens of Covariate Drift","created":"2024-09-19","cited_by_count":3,"area":null},{"id":"2504.19179","title":"A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoption","created":"2025-04-27","cited_by_count":3,"area":null},{"id":"2508.21334","title":"Stairway to Fairness: Connecting Group and Individual Fairness","created":"2025-08-29","cited_by_count":3,"area":null},{"id":"2203.09632","title":"Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages","created":"2022-03-17","cited_by_count":2,"area":null},{"id":"2209.08321","title":"Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances","created":"2022-09-17","cited_by_count":2,"area":null},{"id":"2301.12139","title":"Bipol: Multi-axes Evaluation of Bias with Explainability in Benchmark Datasets","created":"2023-01-28","cited_by_count":2,"area":null},{"id":"2302.00025","title":"On the Within-Group Fairness of Screening Classifiers","created":"2023-01-31","cited_by_count":2,"area":null},{"id":"2303.14665","title":"Achieving Counterfactual Fairness with Imperfect Structural Causal Model","created":"2023-03-26","cited_by_count":2,"area":null},{"id":"2311.02205","title":"An Introduction to Natural Language Processing Techniques and Framework for Clinical Implementation in Radiation Oncology","created":"2023-11-03","cited_by_count":2,"area":null},{"id":"2402.12937","title":"GRAPHGINI: Fostering Individual and Group Fairness in Graph Neural Networks","created":"2024-02-20","cited_by_count":2,"area":null},{"id":"2405.09251","title":"Measuring Model-Induced Discrimination via Efficient Fairness Approximation","created":"2024-05-15","cited_by_count":2,"area":null},{"id":"2407.00400","title":"Formalising Anti-Discrimination Law in Automated Decision Systems","created":"2024-06-29","cited_by_count":2,"area":null},{"id":"2501.11214","title":"Mitigating Spatial Disparity in Urban Prediction Using Residual-Aware Spatiotemporal Graph Neural Networks: A Chicago Case Study","created":"2025-01-20","cited_by_count":2,"area":null},{"id":"2505.08064","title":"Justified Evidence Collection for Argument-based AI Fairness Assurance","created":"2025-05-12","cited_by_count":2,"area":null},{"id":"2506.17035","title":"Critical Appraisal of Fairness Metrics in Clinical Predictive AI","created":"2025-06-20","cited_by_count":2,"area":null},{"id":"2606.18111","title":"Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning","created":"2026-06-16","cited_by_count":2,"area":"deeprl"},{"id":"2103.10510","title":"Hidden Technical Debts for Fair Machine Learning in Financial Services","created":"2021-03-18","cited_by_count":1,"area":null},{"id":"2104.04353","title":"Implementing Fair Regression In The Real World","created":"2021-04-09","cited_by_count":1,"area":null},{"id":"2209.15418","title":"Equitable Marketplace Mechanism Design","created":"2022-09-22","cited_by_count":1,"area":null},{"id":"2301.08375","title":"Within-group fairness: A guidance for more sound between-group fairness","created":"2023-01-20","cited_by_count":1,"area":null},{"id":"2307.05333","title":"Wearable-based Fair and Accurate Pain Assessment Using Multi-Attribute Fairness Loss in Convolutional Neural Networks","created":"2023-07-03","cited_by_count":1,"area":null},{"id":"2401.13391","title":"Reranking individuals: The effect of fair classification within-groups","created":"2024-01-24","cited_by_count":1,"area":null},{"id":"2405.06433","title":"Fair Mixed Effects Support Vector Machine","created":"2024-05-10","cited_by_count":1,"area":null},{"id":"2602.01558","title":"How Implicit Bias Accumulates and Propagates in LLM Long-term Memory","created":"2026-02-02","cited_by_count":1,"area":null},{"id":"2102.11211","title":"Moral Decision-Making in Medical Hybrid Intelligent Systems: A Team Design Patterns Approach to the Bias Mitigation and Data Sharing Design Problems","created":"2021-02-16","cited_by_count":0,"area":null},{"id":"2105.04249","title":"Accounting for Model Uncertainty in Algorithmic Discrimination","created":"2021-05-10","cited_by_count":0,"area":null},{"id":"2107.01277","title":"Non-Comparative Fairness for Human-Auditing and Its Relation to Traditional Fairness Notions","created":"2021-06-29","cited_by_count":0,"area":null},{"id":"2202.01013","title":"Fairness of Machine Learning Algorithms in Demography","created":"2022-02-02","cited_by_count":0,"area":null},{"id":"2202.11966","title":"Impacts of Individual Fairness on Group Fairness from the Perspective of Generalized Entropy","created":"2022-02-24","cited_by_count":0,"area":null},{"id":"2211.14395","title":"Deep Learning Training Procedure Augmentations","created":"2022-11-25","cited_by_count":0,"area":null},{"id":"2304.06901","title":"Systemic Fairness","created":"2023-04-14","cited_by_count":0,"area":null},{"id":"2305.18160","title":"Counterpart Fairness -- Addressing Systematic between-group Differences in Fairness Evaluation","created":"2023-05-29","cited_by_count":0,"area":null},{"id":"2403.12069","title":"Fairness Evaluation for Uplift Modeling in the Absence of Ground Truth","created":"2024-02-12","cited_by_count":0,"area":null},{"id":"2407.03146","title":"Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Game Approach","created":"2024-05-31","cited_by_count":0,"area":null},{"id":"2408.00330","title":"\"Patriarchy Hurts Men Too.\" Does Your Model Agree? A Discussion on Fairness Assumptions","created":"2024-08-01","cited_by_count":0,"area":null},{"id":"2408.06102","title":"Contexts Matter: An Empirical Study on Contextual Influence in Fairness Testing for Deep Learning Systems","created":"2024-08-12","cited_by_count":0,"area":null},{"id":"2506.12556","title":"Algorithmic Fairness: Not a Purely Technical but Socio-Technical Property","created":"2025-06-14","cited_by_count":0,"area":null},{"id":"2508.16377","title":"Applications and Challenges of Fairness APIs in Machine Learning Software","created":"2025-08-22","cited_by_count":0,"area":null},{"id":"2601.16926","title":"Nishpaksh: TEC Standard-Compliant Framework for Fairness Auditing and Certification of AI Models","created":"2026-01-23","cited_by_count":0,"area":null},{"id":"2603.09662","title":"No evaluation without fair representation : Impact of label and selection bias on the evaluation, performance and mitigation of classification models","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2603.21393","title":"A Generalised Exponentiated Gradient Approach to Enhance Fairness in Binary and Multi-class Classification Tasks","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2604.12757","title":"GF-Score: Certified Class-Conditional Robustness Evaluation with Fairness Guarantees","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2606.22858","title":"The Unseen Hand: Manipulating Model Fairness and SHAP with Targeted Identity Re-Association Attacks","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2607.16620","title":"Privacy Cost as Equity Input: A Group Fairness Criterion for Differentially Private Machine Learning","created":"2026-07-18","cited_by_count":0,"area":"safety"},{"id":"2607.26068","title":"The Human Utility Factor: A Computable Welfare Metric That Reframes AI Governance as a Constrained Optimisation Problem","created":"2026-06-23","cited_by_count":0,"area":null},{"id":"2608.00175","title":"Inference-Time Policy Alignment for Fair Reinforcement Learning","created":"2026-07-31","cited_by_count":0,"area":null},{"id":"2608.14568","title":"Position: AI Governance Needs ISO-like Interoperability Protocols, Not Just Laws","created":"2026-05-30","cited_by_count":0,"area":null},{"id":"2608.30223","title":"Fairness in multi-class multi-group classification problems via contextial coherent risk measures","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.36174","title":"Fair Policy Optimization in Major-Minor Weakly Coupled Markov Decision Processes","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}