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Fairness

Papers

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Showing 1301–1350 of 5676 papers

TitleStatusHype
Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Optimization—0
Simultaneous Unlearning of Multiple Protected User Attributes From Variational Autoencoder Recommenders Using Adversarial TrainingCode0
A Systematic Review of Machine Learning in Sports Betting: Techniques, Challenges, and Future Directions—0
FairStream: Fair Multimedia Streaming Benchmark for Reinforcement Learning AgentsCode0
Modelling of Economic Implications of Bias in AI-Powered Health Emergency Response Systems—0
FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits Allocation—0
Exploring Welfare Maximization and Fairness in Participatory Budgeting—0
FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs—0
Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI—0
Most Swiss-system tournaments are unfair: Evidence from chess—0
Balancing the Scales: Enhancing Fairness in Facial Expression Recognition with Latent Alignment—0
From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages—0
Less Discriminatory Alternative and Interpretable XGBoost Framework for Binary Classification—0
FairQueue: Rethinking Prompt Learning for Fair Text-to-Image Generation—0
Learning to Explore with Lagrangians for Bandits under Unknown Linear Constraints—0
From Efficiency to Equity: Measuring Fairness in Preference Learning—0
Learning Fair and Preferable Allocations through Neural Network—0
BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers—0
Testing Deep Learning Recommender Systems Models on Synthetic GAN-Generated Datasets—0
Large Language Models Still Exhibit Bias in Long Text—0
FairDgcl: Fairness-aware Recommendation with Dynamic Graph Contrastive LearningCode0
General Frameworks for Conditional Two-Sample TestingCode0
Revealing Hidden Bias in AI: Lessons from Large Language Models—0
DEAN: Deactivating the Coupled Neurons to Mitigate Fairness-Privacy Conflicts in Large Language ModelsCode0
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection—0
FairLoRA: Unpacking Bias Mitigation in Vision Models with Fairness-Driven Low-Rank Adaptation—0
Revisiting Technical Bias Mitigation Strategies—0
Convex Markov Games: A New Frontier for Multi-Agent Reinforcement Learning—0
End-to-End Optimization and Learning of Fair Court Schedules—0
Trustworthy XAI and Application—0
Finite-Sample and Distribution-Free Fair Classification: Optimal Trade-off Between Excess Risk and Fairness, and the Cost of Group-Blindness—0
Whither Bias Goes, I Will Go: An Integrative, Systematic Review of Algorithmic Bias Mitigation—0
CalibraEval: Calibrating Prediction Distribution to Mitigate Selection Bias in LLMs-as-JudgesCode0
Fairness Evaluation with Item Response Theory—0
Ethical AI in Retail: Consumer Privacy and Fairness—0
Data Augmentation via Diffusion Model to Enhance AI Fairness—0
Who is Undercover? Guiding LLMs to Explore Multi-Perspective Team Tactic in the Game—0
A Semidefinite Relaxation Approach for Fair Graph ClusteringCode0
Text-to-Image Representativity Fairness Evaluation Framework—0
Addressing Blind Guessing: Calibration of Selection Bias in Multiple-Choice Question Answering by Video Language Models—0
LabSafety Bench: Benchmarking LLMs on Safety Issues in Scientific Labs—0
FaceSaliencyAug: Mitigating Geographic, Gender and Stereotypical Biases via Saliency-Based Data Augmentation—0
Pessimistic Evaluation—0
Auditing and Enforcing Conditional Fairness via Optimal Transport—0
The Disparate Benefits of Deep EnsemblesCode0
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective LandscapesCode0
debiaSAE: Benchmarking and Mitigating Vision-Language Model BiasCode0
Fairness-Enhancing Ensemble Classification in Water Distribution NetworksCode0
Advancing Fairness in Natural Language Processing: From Traditional Methods to Explainability—0
Fair Clustering for Data Summarization: Improved Approximation Algorithms and Complexity Insights—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