SOTAVerified

Fairness

Papers

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Showing 2126–2150 of 5676 papers

TitleStatusHype
The Male CEO and the Female Assistant: Evaluation and Mitigation of Gender Biases in Text-To-Image Generation of Dual Subjects—0
Privacy for Fairness: Information Obfuscation for Fair Representation Learning with Local Differential Privacy—0
Towards Cohesion-Fairness Harmony: Contrastive Regularization in Individual Fair Graph ClusteringCode0
FedD2S: Personalized Data-Free Federated Knowledge Distillation—0
FairSync: Ensuring Amortized Group Exposure in Distributed Recommendation RetrievalCode0
"Model Cards for Model Reporting" in 2024: Reclassifying Category of Ethical Considerations in Terms of Trustworthiness and Risk Management—0
Regulating Cryptocurrency and Decentralized Finance for an Inclusive Economy—0
DPBalance: Efficient and Fair Privacy Budget Scheduling for Federated Learning as a Service—0
User Modeling and User Profiling: A Comprehensive Survey—0
Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models—0
Inference for an Algorithmic Fairness-Accuracy Frontier—0
Rate-Splitting Multiple Access for Quantized ISAC LEO Satellite Systems: A Max-Min Fair Energy-Efficient Beam Design—0
Stability and Multigroup Fairness in Ranking with Uncertain Predictions—0
Is my Data in your AI Model? Membership Inference Test with Application to Face Images—0
MaxMin-RLHF: Alignment with Diverse Human Preferences—0
Connecting Algorithmic Fairness to Quality Dimensions in Machine Learning in Official Statistics and Survey Production—0
Causal Learning for Trustworthy Recommender Systems: A Survey—0
Towards Equitable Agile Research and Development of AI and Robotics—0
Fairness Auditing with Multi-Agent CollaborationCode0
Taking Training Seriously: Human Guidance and Management-Based Regulation of Artificial Intelligence—0
A survey of recent methods for addressing AI fairness and bias in biomedicine—0
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review—0
Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated LearningCode0
End-to-End Learning for Fair Multiobjective Optimization Under Uncertainty—0
The Bias of Harmful Label Associations in Vision-Language Models—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