SOTAVerified

Fairness

Papers

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Showing 2176–2200 of 5676 papers

TitleStatusHype
Bias Neutralization Framework: Measuring Fairness in Large Language Models with Bias Intelligence Quotient (BiQ)—0
Ensuring Fairness with Transparent Auditing of Quantitative Bias in AI Systems—0
Ensuring Fairness under Prior Probability Shifts—0
Bias mitigation techniques in image classification: fair machine learning in human heritage collections—0
An Empirical Study on the Fairness of Pre-trained Word Embeddings—0
Advancing Personalized Federated Learning: Group Privacy, Fairness, and Beyond—0
Ensuring Fair LLM Serving Amid Diverse Applications—0
Bias Mitigation Post-processing for Individual and Group Fairness—0
Ensuring Equitable Financial Decisions: Leveraging Counterfactual Fairness and Deep Learning for Bias—0
FairCal: Fairness Calibration for Face Verification—0
Enhancing Trust Through Standards: A Comparative Risk-Impact Framework for Aligning ISO AI Standards with Global Ethical and Regulatory Contexts—0
Enhancing Trust in LLMs: Algorithms for Comparing and Interpreting LLMs—0
Bias Mitigation in Fine-tuning Pre-trained Models for Enhanced Fairness and Efficiency—0
Enhancing transparency in AI-powered customer engagement—0
Enhancing the Fairness and Performance of Edge Cameras with Explainable AI—0
Bias Mitigation Framework for Intersectional Subgroups in Neural Networks—0
An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation—0
Advancing Legal Reasoning: The Integration of AI to Navigate Complexities and Biases in Global Jurisprudence with Semi-Automated Arbitration Processes (SAAPs)—0
Achieving User-Side Fairness in Contextual Bandits—0
Bias in Unsupervised Anomaly Detection in Brain MRI—0
Enhancing Security and Strengthening Defenses in Automated Short-Answer Grading Systems—0
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training—0
Enhancing Recommender System Performance by Histogram Equalization—0
Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling—0
Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation—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