algorithmic fairness

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods ICLR 2024 Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks AAAI 2024 Identifying, Mitigating, and Anticipating Bias in Algorithmic Decisions AAAI 2024 Identifying Reasons for Bias: An Argumentation-Based Approach AAAI 2024 Improving Fairness in Deepfake Detection WACV 2024 Interactive Human-Centric Bias Mitigation AAAI 2024 Interpretable algorithmic fairness in structured and unstructured data JMLR 2024 Is this model reliable for everyone? Testing for strong calibration AISTATS 2024 Language Technologies as If People Mattered: Centering Communities in Language Technology Development COLING 2024 Learning Fair Policies for Multi-Stage Selection Problems from Observational Data AAAI 2024 Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making NeurIPS 2024 Mixed Fair Division: A Survey AAAI 2024 Monoculture in Matching Markets NeurIPS 2024 On the Fairness ROAD: Robust Optimization for Adversarial Debiasing ICLR 2024 OxonFair: A Flexible Toolkit for Algorithmic Fairness NeurIPS 2024 Perceptual Fairness in Image Restoration NeurIPS 2024 Performative Ethics From Within the Ivory Tower: How CSPractitioners Uphold Systems of Oppression (Abstract Reprint) IJCAI 2024 Supervised Algorithmic Fairness in Distribution Shifts: A Survey IJCAI 2024 Temporal Fairness in Multiwinner Voting AAAI 2024 The Impact of Features Used by Algorithms on Perceptions of Fairness IJCAI 2024 Towards Algorithmic Fidelity: Mental Health Representation across Demographics in Synthetic vs. Human-generated Data COLING 2024 Transport-based Counterfactual Models JMLR 2024 Unprocessing Seven Years of Algorithmic Fairness ICLR 2024 User-item fairness tradeoffs in recommendations NeurIPS 2024 When is Multicalibration Post-Processing Necessary? NeurIPS 2024