SOTAVerified

Fairness

Papers

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Showing 1201–1225 of 5676 papers

TitleStatusHype
Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering—0
Inference-Time Selective Debiasing—0
Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects—0
To which reference class do you belong? Measuring racial fairness of reference classes with normative modelingCode0
FairAIED: Navigating Fairness, Bias, and Ethics in Educational AI Applications—0
Fairness Definitions in Language Models ExplainedCode1
Ontology of Belief Diversity: A Community-Based Epistemological Approach—0
Machine Learning for Fairness-Aware Load Shedding: A Real-Time Solution via Identifying Binding Constraints—0
Exploring Bengali Religious Dialect Biases in Large Language Models with Evaluation Perspectives—0
Long-term Fairness in Ride-Hailing Platform—0
Dataset Distribution Impacts Model Fairness: Single vs. Multi-Task Learning—0
Open Challenges on Fairness of Artificial Intelligence in Medical Imaging Applications—0
Hidden or Inferred: Fair Learning-To-Rank with Unknown DemographicsCode0
On ADMM in Heterogeneous Federated Learning: Personalization, Robustness, and FairnessCode0
Multimodal Machine Learning in Mental Health: A Survey of Data, Algorithms, and Challenges—0
Articulation Work and Tinkering for Fairness in Machine Learning—0
Merit-based Fair Combinatorial Semi-Bandit with Unrestricted Feedback DelaysCode0
PUFFLE: Balancing Privacy, Utility, and Fairness in Federated LearningCode0
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution—0
FairViT: Fair Vision Transformer via Adaptive MaskingCode0
Implementing Fairness in AI Classification: The Role of Explainability—0
AI for All: Identifying AI incidents Related to Diversity and Inclusion—0
Justified Fairness in House Allocation Problems: two Characterizations of Strategy-proof Mechanisms—0
Reexamining Racial Disparities in Automatic Speech Recognition Performance: The Role of Confounding by Provenance—0
Thinking Racial Bias in Fair Forgery Detection: Models, Datasets and EvaluationsCode1
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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