SOTAVerified

Fairness

Papers

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Showing 4226–4250 of 5676 papers

TitleStatusHype
Measurement and Fairness—0
Measures of relevance to the success of streaming platforms—0
Measure Twice, Cut Once: Quantifying Bias and Fairness in Deep Neural Networks—0
Measuring algorithmic interpretability: A human-learning-based framework and the corresponding cognitive complexity score—0
Measuring and Mitigating Biases in Motor Insurance Pricing—0
Measuring and signing fairness as performance under multiple stakeholder distributions—0
Measuring a Texts Fairness Dimensions Using Machine Learning Based on Social Psychological Factors—0
Measuring Bias in a Ranked List using Term-based Representations—0
Measuring Commonality in Recommendation of Cultural Content: Recommender Systems to Enhance Cultural Citizenship—0
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition—0
Measuring Ethics in AI with AI: A Methodology and Dataset Construction—0
Measuring Self-Preferencing on Digital Platforms—0
Measuring Fairness in Financial Transaction Machine Learning Models—0
Measuring Fairness in Large-Scale Recommendation Systems with Missing Labels—0
Measuring Fairness of Text Classifiers via Prediction Sensitivity—0
Measuring Fairness of Text Classifiers via Prediction Sensitivity—0
Measuring Fairness with Biased Rulers: A Comparative Study on Bias Metrics for Pre-trained Language Models—0
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments—0
Measuring Machine Learning Harms from Stereotypes Requires Understanding Who Is Harmed by Which Errors in What Ways—0
Measuring Model Biases in the Absence of Ground Truth—0
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective—0
Measuring Representational Harms in Image Captioning—0
Measuring Social Biases of Crowd Workers using Counterfactual Queries—0
Measuring Spiritual Values and Bias of Large Language Models—0
Measuring the right thing: justifying metrics in AI impact assessments—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