SOTAVerified

Fairness

Papers

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Showing 5251–5300 of 5676 papers

TitleStatusHype
Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions—0
Evaluating Trade-offs in Computer Vision Between Attribute Privacy, Fairness and Utility—0
Evaluation Framework for AI Systems in "the Wild"—0
Evaluation of Fairness Trade-offs in Predicting Student Success—0
Evaluation of group fairness measures in student performance prediction problems—0
Everyone deserves their voice to be heard: Analyzing Predictive Gender Bias in ASR Models Applied to Dutch Speech Data—0
Everything is Relative: Understanding Fairness with Optimal Transport—0
Evidence-based explanation to promote fairness in AI systems—0
EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations—0
Evolutionary Multi-Objective Optimisation for Fairness-Aware Self Adjusting Memory Classifiers in Data Streams—0
Evolutionary Reinforcement Learning: A Systematic Review and Future Directions—0
EXAGREE: Towards Explanation Agreement in Explainable Machine Learning—0
Examining Imbalance Effects on Performance and Demographic Fairness of Clinical Language Models—0
Examining risks of racial biases in NLP tools for child protective services—0
Examining the Interplay Between Privacy and Fairness for Speech Processing: A Review and Perspective—0
Example-based Explanations for Random Forests using Machine Unlearning—0
ExCalibR: Expected Calibration of Recommendations—0
Exchanging Lessons Between Algorithmic Fairness and Domain Generalization—0
Experimental Studies in General Game Playing: An Experience Report—0
Expert-Guided Extinction of Toxic Tokens for Debiased Generation—0
Expert-Like Reparameterization of Heterogeneous Pyramid Receptive Fields in Efficient CNNs for Fair Medical Image Classification—0
Experts' View on Challenges and Needs for Fairness in Artificial Intelligence for Education—0
Explainability-Driven Quality Assessment for Rule-Based Systems—0
Explainability for fair machine learning—0
Explainability for identification of vulnerable groups in machine learning models—0
Explainability Is in the Mind of the Beholder: Establishing the Foundations of Explainable Artificial Intelligence—0
Explainable AI for Classifying UTI Risk Groups Using a Real-World Linked EHR and Pathology Lab Dataset—0
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities—0
Explainable AI for Fair Sepsis Mortality Predictive Model—0
Explainable AI is Responsible AI: How Explainability Creates Trustworthy and Socially Responsible Artificial Intelligence—0
Explainable Artificial Intelligence: A Survey of Needs, Techniques, Applications, and Future Direction—0
Explainable artificial intelligence in breast cancer detection and risk prediction: A systematic scoping review—0
Explainable Artificial Intelligence (XAI) from a user perspective- A synthesis of prior literature and problematizing avenues for future research—0
Explainable Deep Reinforcement Learning: State of the Art and Challenges—0
Explainable Disparity Compensation for Efficient Fair Ranking—0
Explainable Fairness in Recommendation—0
Explainable Multi-Stakeholder Job Recommender Systems—0
Explainable post-training bias mitigation with distribution-based fairness metrics—0
Explaining AI Decisions: Towards Achieving Human-Centered Explainability in Smart Home Environments—0
Explaining Algorithmic Fairness Through Fairness-Aware Causal Path Decomposition—0
Explaining how your AI system is fair—0
Explaining Knock-on Effects of Bias Mitigation—0
Explaining Language Models' Predictions with High-Impact Concepts—0
Explaining the data or explaining a model? Shapley values that uncover non-linear dependencies—0
Explanation-Guided Fair Federated Learning for Transparent 6G RAN Slicing—0
Exploiting Cell-Free Massive MIMO for Enabling Simultaneous Wireless Information and Power Transfer—0
Exploiting Fairness to Enhance Sensitive Attributes Reconstruction—0
Exploiting MMD and Sinkhorn Divergences for Fair and Transferable Representation Learning—0
SYNAuG: Exploiting Synthetic Data for Data Imbalance Problems—0
Exploring Accuracy-Fairness Trade-off in Large Language Models—0
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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