SOTAVerified

Fairness

Papers

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Showing 3876–3900 of 5676 papers

TitleStatusHype
Improving Fairness and Privacy in Selection Problems—0
Improving Fairness and Robustness in End-to-End Speech Recognition through unsupervised clustering—0
Improving Fairness for Data Valuation in Horizontal Federated Learning—0
Improving Fairness in Adaptive Social Exergames via Shapley Bandits—0
Improving Fairness in Credit Lending Models using Subgroup Threshold Optimization—0
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets—0
Improving Fairness in Facial Albedo Estimation via Visual-Textual Cues—0
Improving Fairness in Large-Scale Object Recognition by CrowdSourced Demographic Information—0
Improving Fairness in LLMs Through Testing-Time Adversaries—0
Improving fairness in machine learning systems: What do industry practitioners need?—0
Improving Fairness in Photovoltaic Curtailments via Daily Topology Reconfiguration for Voltage Control in Power Distribution Networks—0
Improving Fairness in Speaker Recognition—0
Improving Fairness of AI Systems with Lossless De-biasing—0
Improving Fairness without Demographic by Lagged Dynamic Grouping—0
Improving Fair Training under Correlation Shifts—0
Improving Gender Fairness of Pre-Trained Language Models without Catastrophic Forgetting—0
Improving Large Language Model (LLM) fidelity through context-aware grounding: A systematic approach to reliability and veracity—0
Improving LLM Group Fairness on Tabular Data via In-Context Learning—0
Improving Recommendation Fairness without Sensitive Attributes Using Multi-Persona LLMs—0
Improving Robust Fairness via Balance Adversarial Training—0
Improving the Deferred Acceptance with Minimal Compromise—0
Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models—0
INACIA: Integrating Large Language Models in Brazilian Audit Courts: Opportunities and Challenges—0
Incentive Allocation in Vertical Federated Learning Based on Bankruptcy Problem—0
Incentive-Aware Machine Learning; Robustness, Fairness, Improvement & Causality—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