SOTAVerified

Fairness

Papers

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Showing 2701–2725 of 5676 papers

TitleStatusHype
FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation—0
FedCRL: Personalized Federated Learning with Contrastive Shared Representations for Label Heterogeneity in Non-IID Data—0
FedD2S: Personalized Data-Free Federated Knowledge Distillation—0
FedDriveScore: Federated Scoring Driving Behavior with a Mixture of Metric Distributions—0
FedDRL: Deep Reinforcement Learning-based Adaptive Aggregation for Non-IID Data in Federated Learning—0
Entropy-driven Fair and Effective Federated Learning—0
Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning—0
Fair Kernel Learning—0
Deciding What's Fair: Challenges of Applying Reinforcement Learning in Online Marketplaces—0
Federated Fairness without Access to Sensitive Groups—0
Ensuring Reliability of Curated EHR-Derived Data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) Framework—0
Fair k-Centers via Maximum Matching—0
Federated Learning over a Wireless Network: Distributed User Selection through Random Access—0
Decision Making with Differential Privacy under a Fairness Lens—0
Cluster-level Group Representativity Fairness in k-means Clustering—0
Federated Learning with Fair Worker Selection: A Multi-Round Submodular Maximization Approach—0
Federated Learning with Relative Fairness—0
A Scalable and Generalized Deep Learning Framework for Anomaly Detection in Surveillance Videos—0
Flexibly Fair Representation Learning by Disentanglement—0
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks—0
FederatedTrust: A Solution for Trustworthy Federated Learning—0
Federated Unlearning: a Perspective of Stability and Fairness—0
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data—0
FedFACT: A Provable Framework for Controllable Group-Fairness Calibration in Federated Learning—0
FRAPPE: A Group Fairness Framework for Post-Processing Everything—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