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Fairness

Papers

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Showing 4901–4925 of 5676 papers

TitleStatusHype
Data Representativeness in Accessibility Datasets: A Meta-Analysis—0
Data Representativity for Machine Learning and AI Systems—0
Dataset Distribution Impacts Model Fairness: Single vs. Multi-Task Learning—0
Dataset | Mindset = Explainable AI | Interpretable AI—0
Dataset Representativeness and Downstream Task Fairness—0
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution—0
Datasheets for Machine Learning Sensors: Towards Transparency, Auditability, and Responsibility for Intelligent Sensing—0
Data Trading Combination Auction Mechanism based on the Exponential Mechanism—0
Data vs. Model Machine Learning Fairness Testing: An Empirical Study—0
DBFed: Debiasing Federated Learning Framework based on Domain-Independent—0
D-BIAS: A Causality-Based Human-in-the-Loop System for Tackling Algorithmic Bias—0
Dbias: Detecting biases and ensuring Fairness in news articles—0
De-amplifying Bias from Differential Privacy in Language Model Fine-tuning—0
DeAR: Debiasing Vision-Language Models with Additive Residuals—0
Debate Dynamics for Human-comprehensible Fact-checking on Knowledge Graphs—0
Debias-CLR: A Contrastive Learning Based Debiasing Method for Algorithmic Fairness in Healthcare Applications—0
De-biased Representation Learning for Fairness with Unreliable Labels—0
Debiasing classifiers: is reality at variance with expectation?—0
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model—0
Debiasing Graph Representation Learning based on Information Bottleneck—0
Debiasing Methods for Fairer Neural Models in Vision and Language Research: A Survey—0
Debiasing Neural Retrieval via In-batch Balancing Regularization—0
Debiasing Pretrained Text Encoders by Paying Attention to Paying Attention—0
Debias the Black-box: A Fair Ranking Framework via Knowledge Distillation—0
DECAF: Learning to be Fair in Multi-agent Resource Allocation—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