SOTAVerified

Fairness

Papers

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Showing 951–975 of 5676 papers

TitleStatusHype
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
What is Left After Distillation? How Knowledge Transfer Impacts Fairness and Bias—0
DemoShapley: Valuation of Demonstrations for In-Context Learning—0
COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence ActCode2
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games—0
A Unified Debiasing Approach for Vision-Language Models across Modalities and TasksCode0
Active Fourier Auditor for Estimating Distributional Properties of ML Models—0
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual ExplanationsCode1
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated LearningCode0
Enhancing Legal Case Retrieval via Scaling High-quality Synthetic Query-Candidate PairsCode1
PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning—0
MedImageInsight: An Open-Source Embedding Model for General Domain Medical ImagingCode0
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
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications—0
Stochastic Bandits for Egalitarian Assignment—0
Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models—0
Fair-OBNC: Correcting Label Noise for Fairer DatasetsCode0
Skin Cancer Machine Learning Model Tone Bias—0
Uncertainty-Aware Fairness-Adaptive Classification Trees—0
Rules, Cases, and Reasoning: Positivist Legal Theory as a Framework for Pluralistic AI Alignment—0
FairFML: Fair Federated Machine Learning with a Case Study on Reducing Gender Disparities in Cardiac Arrest Outcome PredictionCode0
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All datasetsBAF – BaseBAF – Variant IBAF – Variant IIBAF – Variant IIIBAF – Variant IVBAF – Variant VDiveFaceMORPHUTKFace

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