SOTAVerified

Fairness

Papers

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Showing 951–1000 of 5676 papers

TitleStatusHype
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains—0
No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users—0
DemoShapley: Valuation of Demonstrations for In-Context Learning—0
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games—0
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual ExplanationsCode1
A Unified Debiasing Approach for Vision-Language Models across Modalities and TasksCode0
Active Fourier Auditor for Estimating Distributional Properties of ML Models—0
COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence ActCode2
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated LearningCode0
Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate PairsCode1
MedImageInsight: An Open-Source Embedding Model for General Domain Medical ImagingCode0
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning—0
Collusion Detection with Graph Neural Networks—0
VHELM: A Holistic Evaluation of Vision Language Models—0
Ethical Leadership in the Age of AI Challenges, Opportunities and Framework for Ethical Leadership—0
Towards an Operational Responsible AI Framework for Learning Analytics in Higher Education—0
Stochastic Bandits for Egalitarian Assignment—0
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications—0
Skin Cancer Machine Learning Model Tone Bias—0
Uncertainty-Aware Fairness-Adaptive Classification Trees—0
Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models—0
Fair-OBNC: Correcting Label Noise for Fairer DatasetsCode0
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome PredictionCode0
Rules, Cases, and Reasoning: Positivist Legal Theory as a Framework for Pluralistic AI Alignment—0
Trained Models Tell Us How to Make Them Robust to Spurious Correlation without Group AnnotationCode0
Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation—0
GLEE: A Unified Framework and Benchmark for Language-based Economic EnvironmentsCode0
Social Choice for Heterogeneous Fairness in Recommendation—0
Collapsed Language Models Promote FairnessCode0
Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks—0
Towards TMA-Based Transmissive RIS Transceiver Enabled Downlink Communication Networks: A Consensus-ADMM Approach—0
A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future ResearchCode0
Group Fairness in Peer Review—0
Understanding Decision Subjects' Engagement with and Perceived Fairness of AI Models When Opportunities of Qualification Improvement Exist—0
Overcoming Representation Bias in Fairness-Aware data Repair using Optimal Transport—0
PFGuard: A Generative Framework with Privacy and Fairness Safeguards—0
Minimax Group Fairness in Strategic Classification—0
Fair Decentralized LearningCode0
Harm Ratio: A Novel and Versatile Fairness Criterion—0
Achieving Fairness in Predictive Process Analytics via Adversarial Learning—0
Conformal Prediction Sets Can Cause Disparate ImpactCode0
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated LearningCode0
FairlyUncertain: A Comprehensive Benchmark of Uncertainty in Algorithmic Fairness—0
Causal Inference Tools for a Better Evaluation of Machine Learning—0
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups—0
Fair4Free: Generating High-fidelity Fair Synthetic Samples using Data Free Distillation—0
Fair Class-Incremental Learning using Sample Weighting—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications—0
Explainable Multi-Stakeholder Job Recommender Systems—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.86—Unverified
21D-CSNNPredictive Equality (age)97.8—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)96.87—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.97—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.45—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)98.68—Unverified
#ModelMetricClaimedVerifiedStatus
11D-CSNNPredictive Equality (age)99.31—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)6.26—Unverified
#ModelMetricClaimedVerifiedStatus
1Neighbour LearningDegree of Bias (DoB)1.96—Unverified