SOTAVerified

Fairness

Papers

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Showing 2201–2225 of 5676 papers

TitleStatusHype
Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification—0
Advancing Fairness in Natural Language Processing: From Traditional Methods to Explainability—0
Enhancing Model Fairness and Accuracy with Similarity Networks: A Methodological Approach—0
Enhancing Logical Reasoning in Large Language Models to Facilitate Legal Applications—0
Biasing & Debiasing based Approach Towards Fair Knowledge Transfer for Equitable Skin Analysis—0
Enhancing kidney transplantation through multi-agent kidney exchange programs: A comprehensive review and optimization models—0
Bias in AI-systems: A multi-step approach—0
Friends in Unexpected Places: Enhancing Local Fairness in Federated Learning through Clustering—0
Enhancing Federated Learning Through Secure Cluster-Weighted Client Aggregation—0
Enhancing Fairness through Reweighting: A Path to Attain the Sufficiency Rule—0
BiasGuard: A Reasoning-enhanced Bias Detection Tool For Large Language Models—0
An Empirical Study of Modular Bias Mitigators and Ensembles—0
Advancing Cultural Inclusivity: Optimizing Embedding Spaces for Balanced Music Recommendations—0
Achieving Transparency Report Privacy in Linear Time—0
BiasFilter: An Inference-Time Debiasing Framework for Large Language Models—0
Learning Fairer Representations with FairVIC—0
Travel Demand Forecasting: A Fair AI Approach—0
Bias, Fairness, and Accountability with AI and ML Algorithms—0
Enhancing Fairness and Performance in Machine Learning Models: A Multi-Task Learning Approach with Monte-Carlo Dropout and Pareto Optimality—0
Balancing Efficiency and Equity in Classroom Assignment under Endogenous Peer Effects—0
Enhancing Convergence, Privacy and Fairness for Wireless Personalized Federated Learning: Quantization-Assisted Min-Max Fair Scheduling—0
Understanding and Reducing the Class-Dependent Effects of Data Augmentation with A Two-Player Game Approach—0
Biases in Expected Goals Models Confound Finishing Ability—0
Biases in Edge Language Models: Detection, Analysis, and Mitigation—0
Enhancing Breast Cancer Diagnosis in Mammography: Evaluation and Integration of Convolutional Neural Networks and Explainable AI—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