SOTAVerified

Fairness

Papers

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Showing 4176–4200 of 5676 papers

TitleStatusHype
Machine Learning for Fairness-Aware Load Shedding: A Real-Time Solution via Identifying Binding Constraints—0
Machine Learning for Predictive On-Demand Deployment of UAVs for Wireless Communications—0
Machine Learning for Synthetic Data Generation: A Review—0
Bias in Machine Learning Models Can Be Significantly Mitigated by Careful Training: Evidence from Neuroimaging Studies—0
Machine Learning-Powered Course Allocation—0
Machine Learning Techniques with Fairness for Prediction of Completion of Drug and Alcohol Rehabilitation—0
Machine Learning Testing: Survey, Landscapes and Horizons—0
MAFE: Multi-Agent Fair Environments for Decision-Making Systems—0
MAFT: Efficient Model-Agnostic Fairness Testing for Deep Neural Networks via Zero-Order Gradient Search—0
MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization—0
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings—0
Maintaining Journalistic Integrity in the Digital Age: A Comprehensive NLP Framework for Evaluating Online News Content—0
Making Good on LSTMs' Unfulfilled Promise—0
Making Machine Learning Datasets and Models FAIR for HPC: A Methodology and Case Study—0
Making ML models fairer through explanations: the case of LimeOut—0
MALIBU Benchmark: Multi-Agent LLM Implicit Bias Uncovered—0
Malign Overfitting: Interpolation Can Provably Preclude Invariance—0
Managing Basis Risks in Weather Parametric Insurance: A Quantitative Study of Diversification and Key Influencing Factors—0
Managing Bias in Human-Annotated Data: Moving Beyond Bias Removal—0
Manifestations of Xenophobia in AI Systems—0
Mapping the Ethics of Generative AI: A Comprehensive Scoping Review—0
Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic—0
Mapping the Potential of Explainable AI for Fairness Along the AI Lifecycle—0
Mapping Trustworthiness in Large Language Models: A Bibliometric Analysis Bridging Theory to Practice—0
Marginal Debiased Network for Fair Visual Recognition—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