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Fairness

Papers

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Showing 1901–1925 of 5676 papers

TitleStatusHype
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle—0
FALE: Fairness-Aware ALE Plots for Auditing Bias in Subgroups—0
Predicting Fairness of ML Software Configurations—0
Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)—0
Learning Fairer Representations with FairVIC—0
A Comparison of Differential Performance Metrics for the Evaluation of Automatic Speaker Verification Fairness—0
A Taxation Perspective for Fair Re-rankingCode0
FedCRL: Personalized Federated Learning with Contrastive Shared Representations for Label Heterogeneity in Non-IID Data—0
Bridging the Fairness Divide: Achieving Group and Individual Fairness in Graph Neural Networks—0
Lazy Data Practices Harm Fairness ResearchCode0
Algorithmic Fairness: A Tolerance Perspective—0
FairGT: A Fairness-aware Graph TransformerCode0
mlr3summary: Concise and interpretable summaries for machine learning modelsCode0
Structured Reinforcement Learning for Delay-Optimal Data Transmission in Dense mmWave Networks—0
Conditional Fairness for Generative AIsCode0
Joint operation of a fast-charging EV hub with a stand-alone independent battery storage system under fairness considerations—0
FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication—0
Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments—0
Sum of Group Error Differences: A Critical Examination of Bias Evaluation in Biometric Verification and a Dual-Metric MeasureCode0
Identifying Fairness Issues in Automatically Generated Testing Content—0
Machine Learning Techniques with Fairness for Prediction of Completion of Drug and Alcohol Rehabilitation—0
Fair Concurrent Training of Multiple Models in Federated Learning—0
Fairness Incentives in Response to Unfair Dynamic Pricing—0
Bt-GAN: Generating Fair Synthetic Healthdata via Bias-transforming Generative Adversarial Networks—0
Enforcing Conditional Independence for Fair Representation Learning and Causal Image Generation—0
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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