SOTAVerified

Fairness

Papers

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Showing 401–425 of 5676 papers

TitleStatusHype
Gender and content bias in Large Language Models: a case study on Google Gemini 2.0 Flash Experimental—0
OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender System—0
VeriContaminated: Assessing LLM-Driven Verilog Coding for Data Contamination—0
Cohort-attention Evaluation Metric against Tied Data: Studying Performance of Classification Models in Cancer Detection—0
Scalable Min-Max Optimization via Primal-Dual Exact Pareto Optimization—0
Unveiling Pitfalls: Understanding Why AI-driven Code Agents Fail at GitHub Issue Resolution—0
Negotiative Alignment: Embracing Disagreement to Achieve Fairer Outcomes -- Insights from Urban Studies—0
Debiasing Diffusion Model: Enhancing Fairness through Latent Representation Learning in Stable Diffusion Model—0
Optimal Hybrid Transmit Beamforming for mm-Wave Integrated Sensing and Communication—0
FedTilt: Towards Multi-Level Fairness-Preserving and Robust Federated Learning—0
A Multi-Objective Evaluation Framework for Analyzing Utility-Fairness Trade-Offs in Machine Learning Systems—0
LLM Agents for Education: Advances and Applications—0
Statistical Impossibility and Possibility of Aligning LLMs with Human Preferences: From Condorcet Paradox to Nash EquilibriumCode0
The Role of Hyperparameters in Predictive Multiplicity—0
Identifying Trustworthiness Challenges in Deep Learning Models for Continental-Scale Water Quality Prediction—0
FedPCA: Noise-Robust Fair Federated Learning via Performance-Capacity Analysis—0
PluralLLM: Pluralistic Alignment in LLMs via Federated Learning—0
SciHorizon: Benchmarking AI-for-Science Readiness from Scientific Data to Large Language Models—0
EquiPy: Sequential Fairness using Optimal Transport in Python—0
Group-robust Machine UnlearningCode0
Mitigating Membership Inference Vulnerability in Personalized Federated Learning—0
Fair Federated Medical Image Classification Against Quality Shift via Inter-Client Progressive State MatchingCode1
Llms, Virtual Users, and Bias: Predicting Any Survey Question Without Human Data—0
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation MethodsCode0
Learning Pareto manifolds in high dimensions: How can regularization help?—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