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Fairness

Papers

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Showing 3651–3700 of 5676 papers

TitleStatusHype
FNAS: Uncertainty-Aware Fast Neural Architecture Search—0
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data—0
Formalising Anti-Discrimination Law in Automated Decision Systems—0
FORML: Learning to Reweight Data for Fairness—0
Fortifying Federated Learning Towards Trustworthiness via Auditable Data Valuation and Verifiable Client Contribution—0
Foundation Models Meet Visualizations: Challenges and Opportunities—0
Efficient and fair trading algorithms in market design environments—0
Fractional Top Trading Cycle on the Full Preference Domain—0
FRAMM: Fair Ranking with Missing Modalities for Clinical Trial Site Selection—0
FRAPPE: A Group Fairness Framework for Post-Processing Everything—0
FreqX: Analyze the Attribution Methods in Another Domain—0
FR-GAN: Fair and Robust Training—0
FROG: Fair Removal on Graphs—0
From Coders to Critics: Empowering Students through Peer Assessment in the Age of AI Copilots—0
From Data to Action: Charting A Data-Driven Path to Combat Antimicrobial Resistance—0
From Deception to Perception: The Surprising Benefits of Deepfakes for Detecting, Measuring, and Mitigating Bias—0
From Discrete to Continuous: Deep Fair Clustering With Transferable Representations—0
From Efficiency to Equity: Measuring Fairness in Preference Learning—0
From English-Centric to Effective Bilingual: LLMs with Custom Tokenizers for Underrepresented Languages—0
From Expectation to Habit: Why Do Software Practitioners Adopt Fairness Toolkits?—0
From Fair Decision Making to Social Equality—0
From Fairness to Infinity: Outcome-Indistinguishable (Omni)Prediction in Evolving Graphs—0
From Fairness to Truthfulness: Rethinking Data Valuation Design—0
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling—0
From Learning to Relearning: A Framework for Diminishing Bias in Social Robot Navigation—0
From Models to Systems: A Comprehensive Fairness Framework for Compositional Recommender Systems—0
From Pixels to Words: Leveraging Explainability in Face Recognition through Interactive Natural Language Processing—0
From Single Aircraft to Communities: A Neutral Interpretation of Air Traffic Complexity Dynamics—0
From Structured Prompts to Open Narratives: Measuring Gender Bias in LLMs Through Open-Ended Storytelling—0
From Texts to Shields: Convergence of Large Language Models and Cybersecurity—0
From Utilitarian to Rawlsian Designs for Algorithmic Fairness—0
Front-door Adjustment Beyond Markov Equivalence with Limited Graph Knowledge—0
Full-Scale Indexing and Semantic Annotation of CT Imaging: Boosting FAIRness—0
Functionality learning through specification instructions—0
Function Composition in Trustworthy Machine Learning: Implementation Choices, Insights, and Questions—0
Fundamental Limits and Tradeoffs in Invariant Representation Learning—0
Fundus2Globe: Generative AI-Driven 3D Digital Twins for Personalized Myopia Management—0
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging—0
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare—0
Games for Fairness and Interpretability—0
Gaussian Harmony: Attaining Fairness in Diffusion-based Face Generation Models—0
Gender and content bias in Large Language Models: a case study on Google Gemini 2.0 Flash Experimental—0
Gender and Racial Fairness in Depression Research using Social Media—0
GenderBias-VL: Benchmarking Gender Bias in Vision Language Models via Counterfactual Probing—0
Gender bias Evaluation in Luganda-English Machine Translation—0
Gender Bias in Machine Translation and The Era of Large Language Models—0
Gender Bias in Text: Origin, Taxonomy, and Implications—0
Gender Bias in Transformer Models: A comprehensive survey—0
Gender Bias of LLM in Economics: An Existentialism Perspective—0
Degendering Resumes for Fair Algorithmic Resume Screening—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