SOTAVerified

Fairness

Papers

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Showing 1701–1725 of 5676 papers

TitleStatusHype
PI-Whisper: Designing an Adaptive and Incremental Automatic Speech Recognition System for Edge Devices—0
Full-Scale Indexing and Semantic Annotation of CT Imaging: Boosting FAIRness—0
I don't trust you (anymore)! -- The effect of students' LLM use on Lecturer-Student-Trust in Higher Education—0
A Unified Framework for Input Feature Attribution Analysis—0
Rate-Splitting Multiple Access for Overloaded Multi-group Multicast: A First Experimental Study—0
Pareto-Optimal Learning from Preferences with Hidden Context—0
FairX: A comprehensive benchmarking tool for model analysis using fairness, utility, and explainabilityCode0
Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models—0
Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs—0
Fair Streaming Feature Selection—0
Active Learning for Fair and Stable Online Allocations—0
Watching the Watchers: A Comparative Fairness Audit of Cloud-based Content Moderation Services—0
Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing ApproachCode0
On the Consistency of Fairness Measurement Methods for Regression Tasks—0
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive AttributesCode0
A Resource-Adaptive Approach for Federated Learning under Resource-Constrained Environments—0
LLM4Rerank: LLM-based Auto-Reranking Framework for Recommendations—0
An Empirical Study on the Fairness of Foundation Models for Multi-Organ Image Segmentation—0
Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Models—0
They're All Doctors: Synthesizing Diverse Counterfactuals to Mitigate Associative Bias—0
Transparency, Privacy, and Fairness in Recommender Systems—0
Slicing Through Bias: Explaining Performance Gaps in Medical Image Analysis using Slice Discovery MethodsCode0
The Benefits and Risks of Transductive Approaches for AI Fairness—0
Grade Score: Quantifying LLM Performance in Option SelectionCode0
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives—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