Fairness
1185 papers with code • 3 benchmarks • 20 datasets
Benchmarks
These leaderboards are used to track progress in Fairness
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Libraries
Use these libraries to find Fairness models and implementations
Netflix Prize
UTKFace
MORPH
FairFace
WinoBias
GVGAI
HELP
MIAP
Latest papers
A Taxation Perspective for Fair Re-ranking
From a taxation perspective, we theoretically demonstrate that most previous fair re-ranking methods can be reformulated as an item-level tax policy.
Lazy Data Practices Harm Fairness Research
Data practices shape research and practice on fairness in machine learning (fair ML).
FairGT: A Fairness-aware Graph Transformer
The design of Graph Transformers (GTs) generally neglects considerations for fairness, resulting in biased outcomes against certain sensitive subgroups.
mlr3summary: Concise and interpretable summaries for machine learning models
This work introduces a novel R package for concise, informative summaries of machine learning models.
Global Concept Explanations for Graphs by Contrastive Learning
aimat-lab/megan_global_explanations
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Overall, our results show promising capability to extract the underlying structure-property relationships for complex graph property prediction tasks.
Formal Specification, Assessment, and Enforcement of Fairness for Generative AIs
Reinforcing or even exacerbating societal biases and inequalities will increase significantly as generative AI increasingly produces useful artifacts, from text to images and beyond, for the real world.
SynthEval: A Framework for Detailed Utility and Privacy Evaluation of Tabular Synthetic Data
With the growing demand for synthetic data to address contemporary issues in machine learning, such as data scarcity, data fairness, and data privacy, having robust tools for assessing the utility and potential privacy risks of such data becomes crucial.
Unveiling and Mitigating Generalized Biases of DNNs through the Intrinsic Dimensions of Perceptual Manifolds
Building fair deep neural networks (DNNs) is a crucial step towards achieving trustworthy artificial intelligence.
Unifying Bias and Unfairness in Information Retrieval: A Survey of Challenges and Opportunities with Large Language Models
With the rapid advancement of large language models (LLMs), information retrieval (IR) systems, such as search engines and recommender systems, have undergone a significant paradigm shift.
FairSSD: Understanding Bias in Synthetic Speech Detectors
In this work, we examine bias in existing synthetic speech detectors to determine if they will unfairly target a particular gender, age and accent group.
