SOTAVerified

Fairness

Papers

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Showing 1376–1400 of 5676 papers

TitleStatusHype
Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games—0
VHELM: A Holistic Evaluation of Vision Language Models—0
Benchmarking Data Heterogeneity Evaluation Approaches for Personalized Federated LearningCode0
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
Stochastic Bandits for Egalitarian Assignment—0
Skin Cancer Machine Learning Model Tone Bias—0
Fair-OBNC: Correcting Label Noise for Fairer DatasetsCode0
Ethical Leadership in the Age of AI Challenges, Opportunities and Framework for Ethical Leadership—0
Sparse Repellency for Shielded Generation in Text-to-image Diffusion Models—0
Uncertainty-Aware Fairness-Adaptive Classification Trees—0
FAIREDU: A Multiple Regression-Based Method for Enhancing Fairness in Machine Learning Models for Educational Applications—0
Towards an Operational Responsible AI Framework for Learning Analytics in Higher Education—0
GLEE: A Unified Framework and Benchmark for Language-based Economic EnvironmentsCode0
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
Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation—0
Trained Models Tell Us How to Make Them Robust to Spurious Correlation without Group AnnotationCode0
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
Group Fairness in Peer Review—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
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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