SOTAVerified

Fairness

Papers

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Showing 4451–4475 of 5676 papers

TitleStatusHype
Attribute-Centric Compositional Text-to-Image Generation—0
Attribution Projection Calculus: A Novel Framework for Causal Inference in Bayesian Networks—0
A Turing Test: Are AI Chatbots Behaviorally Similar to Humans?—0
A Tutorial On Intersectionality in Fair Rankings—0
Auction-Based Scheduling—0
Auditing Algorithmic Fairness in Machine Learning for Health with Severity-Based LOGAN—0
Auditing and Achieving Intersectional Fairness in Classification Problems—0
Auditing and Enforcing Conditional Fairness via Optimal Transport—0
Auditing the Imputation Effect on Fairness of Predictive Analytics in Higher Education—0
Auditing ICU Readmission Rates in an Clinical Database: An Analysis of Risk Factors and Clinical Outcomes—0
Auditing Predictive Models for Intersectional Biases—0
Auditing the Fairness of the US COVID-19 Forecast Hub's Case Prediction Models—0
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness—0
A Unified Approach to Fair Online Learning via Blackwell Approachability—0
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices—0
A Unified Deterministic Channel Model for Multi-Type RIS with Reflective, Transmissive, and Polarization Operations—0
A Unified Framework for Evaluating the Effectiveness and Enhancing the Transparency of Explainable AI Methods in Real-World Applications—0
A Unified Framework for Fair Spectral Clustering With Effective Graph Learning—0
A Unified Framework for Input Feature Attribution Analysis—0
Probabilistic ML Verification via Weighted Model Integration—0
A Unified View of Group Fairness Tradeoffs Using Partial Information Decomposition—0
Tensor Completion with Provable Consistency and Fairness Guarantees for Recommender Systems—0
Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts—0
DP-SGD-Global-Adapt-V2-S: Triad Improvements of Privacy, Accuracy and Fairness via Step Decay Noise Multiplier and Step Decay Upper Clipping Threshold—0
Auto-Drafting Police Reports from Noisy ASR Outputs: A Trust-Centered LLM Approach—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