SOTAVerified

Fairness

Papers

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Showing 1026–1050 of 5676 papers

TitleStatusHype
Reconciling Predictive Multiplicity in PracticeCode0
Value-oriented forecast reconciliation for renewables in electricity markets—0
AI-assisted German Employment Contract Review: A Benchmark Dataset—0
Be Intentional About Fairness!: Fairness, Size, and Multiplicity in the Rashomon Set—0
Optimal Transport on Categorical Data for Counterfactuals using Compositional Data and Dirichlet TransportCode0
Fairness in LLM-Generated Surveys—0
A Post-Processing-Based Fair Federated Learning Framework—0
Fairness-aware Contextual Dynamic Pricing with Strategic Buyers—0
SoK: What Makes Private Learning Unfair?—0
Fairness of Deep Ensembles: On the interplay between per-group task difficulty and under-representation—0
Unlocking the Black Box: Analysing the EU Artificial Intelligence Act's Framework for Explainability in AI—0
Locality-aware Fair Scheduling in LLM Serving—0
Automatic Link Selection in Multi-Channel Multiple Access with Link Failures—0
Overcoming Fairness Trade-offs via Pre-processing: A Causal Perspective—0
Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation ClassifiersCode0
AdEval: Alignment-based Dynamic Evaluation to Mitigate Data Contamination in Large Language Models—0
Perceived Fairness of the Machine Learning Development Process: Concept Scale Development—0
Algorithmic Inheritance: Surname Bias in AI Decisions Reinforces Intergenerational InequalityCode0
It's complicated. The relationship of algorithmic fairness and non-discrimination regulations for high-risk systems in the EU AI Act—0
Enhancing Multi-Attribute Fairness in Healthcare Predictive Modeling—0
Paper Quality Assessment based on Individual Wisdom Metrics from Open Peer Review—0
A Comprehensive Social Bias Audit of Contrastive Vision Language Models—0
Enhancing Robust Fairness via Confusional Spectral RegularizationCode0
Addressing Bias in Generative AI: Challenges and Research Opportunities in Information Management—0
On the "Illusion" of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes—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