SOTAVerified

Fairness

Papers

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Showing 476–500 of 5676 papers

TitleStatusHype
LumiCRS: Asymmetric Contrastive Prototype Learning for Long-Tail Conversational Movie Recommendation—0
BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization—0
IndianBailJudgments-1200: A Multi-Attribute Dataset for Legal NLP on Indian Bail Orders—0
Is Reasoning All You Need? Probing Bias in the Age of Reasoning Language Models—0
MateInfoUB: A Real-World Benchmark for Testing LLMs in Competitive, Multilingual, and Multimodal Educational Tasks—0
Evaluating the Promise and Pitfalls of LLMs in Hiring Decisions—0
Why Multi-Interest Fairness Matters: Hypergraph Contrastive Multi-Interest Learning for Fair Conversational Recommender SystemCode0
FeDa4Fair: Client-Level Federated Datasets for Fairness Evaluation—0
Artificial Delegates Resolve Fairness Issues in Perpetual Voting with Partial Turnout—0
Demonstration of effective UCB-based routing in skill-based queues on real-world data—0
Producer-Fairness in Sequential Bundle Recommendation—0
Peer-to-Peer Energy Markets With Uniform Pricing: A Dynamic Operating Envelope Approach—0
Causal-Aware Intelligent QoE Optimization for VR Interaction with Adaptive Keyframe Extraction—0
Visibly Fair Mechanisms—0
Multimodal Visual Image Based User Association and Beamforming Using Graph Neural Networks—0
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective—0
Reading Smiles: Proxy Bias in Foundation Models for Facial Emotion Recognition—0
An Axiomatization of the Random Priority Rule—0
Soft decision trees for survival analysis—0
Client Selection Strategies for Federated Semantic Communications in Heterogeneous IoT Networks—0
AI based Content Creation and Product Recommendation Applications in E-commerce: An Ethical overview—0
What Is the Point of Equality in Machine Learning Fairness? Beyond Equality of Opportunity—0
Fair Contracts in Principal-Agent Games with Heterogeneous Types—0
Computational Studies in Influencer Marketing: A Systematic Literature Review—0
Fair for a few: Improving Fairness in Doubly Imbalanced Datasets—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