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Fairness

Papers

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Showing 501–550 of 5676 papers

TitleStatusHype
Computational Studies in Influencer Marketing: A Systematic Literature Review—0
One Size Fits None: Rethinking Fairness in Medical AI—0
Fair for a few: Improving Fairness in Doubly Imbalanced Datasets—0
Compositional Attribute Imbalance in Vision Datasets—0
Equitable Electronic Health Record Prediction with FAME: Fairness-Aware Multimodal Embedding—0
Meta Optimality for Demographic Parity Constrained Regression via Post-Processing—0
Towards Fairness Assessment of Dutch Hate Speech Detection—0
Fairness Research For Machine Learning Should Integrate Societal Considerations—0
Semantic Scheduling for LLM InferenceCode0
Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis—0
Bias Amplification in RAG: Poisoning Knowledge Retrieval to Steer LLMs—0
Preserving Task-Relevant Information Under Linear Concept Removal—0
Balancing Tails when Comparing Distributions: Comprehensive Equity Index (CEI) with Application to Bias Evaluation in Operational Face Biometrics—0
Robustly Improving LLM Fairness in Realistic Settings via InterpretabilityCode0
Surface Fairness, Deep Bias: A Comparative Study of Bias in Language Models—0
Size-adaptive Hypothesis Testing for FairnessCode0
FairASR: Fair Audio Contrastive Learning for Automatic Speech Recognition—0
Towards Responsible AI: Advances in Safety, Fairness, and Accountability of Autonomous Systems—0
GRAIL: A Benchmark for GRaph ActIve Learning in Dynamic Sensing Environments—0
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning ApproachCode0
Hateful Person or Hateful Model? Investigating the Role of Personas in Hate Speech Detection by Large Language Models—0
Towards Class-wise Fair Adversarial Training via Anti-Bias Soft Label DistillationCode0
Convergence of Spectral Principal Paths: How Deep Networks Distill Linear Representations from Noisy Inputs—0
Societal AI Research Has Become Less Interdisciplinary—0
Towards Fair Representation: Clustering and Consensus—0
Fairness is Not Silence: Unmasking Vacuous Neutrality in Small Language Models—0
FAIRTOPIA: Envisioning Multi-Agent Guardianship for Disrupting Unfair AI Pipelines—0
FairDICE: Fairness-Driven Offline Multi-Objective Reinforcement Learning—0
Design and Evaluation of Deep Learning-Based Dual-Spectrum Image Fusion Methods—0
Hidden Bias in the Machine: Stereotypes in Text-to-Image Models—0
Addressing Correlated Latent Exogenous Variables in Debiased Recommender SystemsCode0
Fairness Overfitting in Machine Learning: An Information-Theoretic Perspective—0
Statistical Hypothesis Testing for Auditing Robustness in Language Models—0
Improving Fairness of Large Language Models in Multi-document SummarizationCode0
Learning-Based Multiuser Scheduling in MIMO-OFDM Systems with Hybrid Beamforming—0
Accelerating Spectral Clustering under Fairness Constraints—0
Ensuring Reliability of Curated EHR-Derived Data: The Validation of Accuracy for LLM/ML-Extracted Information and Data (VALID) Framework—0
FairPFN: A Tabular Foundation Model for Causal FairnessCode0
fairmetrics: An R package for group fairness evaluation—0
CO-VADA: A Confidence-Oriented Voice Augmentation Debiasing Approach for Fair Speech Emotion Recognition—0
Information Bargaining: Bilateral Commitment in Bayesian PersuasionCode0
The World of AI: A Novel Approach to AI Literacy for First-year Engineering Students—0
EMO-Debias: Benchmarking Gender Debiasing Techniques in Multi-Label Speech Emotion Recognition—0
FG 2025 TrustFAA: the First Workshop on Towards Trustworthy Facial Affect Analysis: Advancing Insights of Fairness, Explainability, and Safety (TrustFAA)—0
Spectral Efficiency Maximization for mmWave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints—0
Composing Agents to Minimize Worst-case RiskCode0
Crowd-SFT: Crowdsourcing for LLM Alignment—0
Learning Fair And Effective Points-Based Rewards Programs—0
When Fairness Isn't Statistical: The Limits of Machine Learning in Evaluating Legal Reasoning—0
CLAIM: An Intent-Driven Multi-Agent Framework for Analyzing Manipulation in Courtroom DialoguesCode0
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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