SOTAVerified

Fairness

Papers

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Showing 1401–1425 of 5676 papers

TitleStatusHype
Towards TMA-Based Transmissive RIS Transceiver Enabled Downlink Communication Networks: A Consensus-ADMM Approach—0
PFGuard: A Generative Framework with Privacy and Fairness Safeguards—0
Minimax Group Fairness in Strategic Classification—0
Achieving Fairness in Predictive Process Analytics via Adversarial Learning—0
Fair Decentralized LearningCode0
Harm Ratio: A Novel and Versatile Fairness Criterion—0
Overcoming Representation Bias in Fairness-Aware data Repair using Optimal Transport—0
Causal Inference Tools for a Better Evaluation of Machine Learning—0
Fair4Free: Generating High-fidelity Fair Synthetic Samples using Data Free Distillation—0
Fair Class-Incremental Learning using Sample Weighting—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Unveiling AI's Potential Through Tools, Techniques, and Applications—0
FairlyUncertain: A Comprehensive Benchmark of Uncertainty in Algorithmic Fairness—0
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated LearningCode0
Conformal Prediction Sets Can Cause Disparate ImpactCode0
ProxiMix: Enhancing Fairness with Proximity Samples in Subgroups—0
Explainable Multi-Stakeholder Job Recommender Systems—0
FMBench: Benchmarking Fairness in Multimodal Large Language Models on Medical Tasks—0
Evaluating the fairness of task-adaptive pretraining on unlabeled test data before few-shot text classificationCode0
Best Practices for Responsible Machine Learning in Credit ScoringCode0
DCAST: Diverse Class-Aware Self-Training Mitigates Selection Bias for Fairer LearningCode0
A large-scale operational study of fingerprint quality and demographics—0
Positive-Sum Fairness: Leveraging Demographic Attributes to Achieve Fair AI Outcomes Without Sacrificing Group Gains—0
Does RAG Introduce Unfairness in LLMs? Evaluating Fairness in Retrieval-Augmented Generation SystemsCode0
Fairness Analysis with Shapley-Owen Effects—0
Differential privacy enables fair and accurate AI-based analysis of speech disorders while protecting patient data—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