Image de couverture de livre

Inference-Time Rule Eraser: Fair Recognition via Distilling and Removing Biased Rules

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhang, Yi, Lu, Dongyuan, Sang, Jitao
Format:	Preprint
Publié:	2024
Sujets:	Machine Learning Artificial Intelligence Computers and Society
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Backdoor for Debias: Mitigating Model Bias with Backdoor Attack-based Artificial Bias
par: Wu, Shangxi, et autres
Publié: (2023)

Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
par: Shieh, Evan, et autres
Publié: (2024)

FairDD: Fair Dataset Distillation
par: Zhou, Qihang, et autres
Publié: (2024)

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
par: Qiu, Xiangfei, et autres
Publié: (2024)

A Post-Processing-Based Fair Federated Learning Framework
par: Zhou, Yi, et autres
Publié: (2025)

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
par: Liu, Pengxi, et autres
Publié: (2025)

Procedural Fairness via Group Counterfactual Explanation
par: Popoola, Gideon, et autres
Publié: (2026)

Health Insurance Coverage Rule Interpretation Corpus: Law, Policy, and Medical Guidance for Health Insurance Coverage Understanding
par: Gartner, Mike
Publié: (2025)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
par: Han, Xiaotian, et autres
Publié: (2023)

Multi-Output Distributional Fairness via Post-Processing
par: Li, Gang, et autres
Publié: (2024)

Fairness in Federated Learning: Fairness for Whom?
par: Taik, Afaf, et autres
Publié: (2025)

Learning Aggregation Rules in Participatory Budgeting: A Data-Driven Approach
par: Fairstein, Roy, et autres
Publié: (2024)

Data Augmentation via Diffusion Model to Enhance AI Fairness
par: Blow, Christina Hastings, et autres
Publié: (2024)

BaBE: Enhancing Fairness via Estimation of Latent Explaining Variables
par: Binkyte, Ruta, et autres
Publié: (2023)

OxonFair: A Flexible Toolkit for Algorithmic Fairness
par: Delaney, Eoin, et autres
Publié: (2024)

FairPFN: Transformers Can do Counterfactual Fairness
par: Robertson, Jake, et autres
Publié: (2024)

FairMT: Fairness for Heterogeneous Multi-Task Learning
par: Hu, Guanyu, et autres
Publié: (2025)

Fair CCA for Fair Representation Learning: An ADNI Study
par: Hou, Bojian, et autres
Publié: (2025)

AI Biases as Asymmetries: A Review to Guide Practice
par: Waters, Gabriella, et autres
Publié: (2025)

Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
par: Alamdari, Parand A., et autres
Publié: (2023)

Fair Text-to-Image Diffusion via Fair Mapping
par: Li, Jia, et autres
Publié: (2023)

Asking For It: Question-Answering for Predicting Rule Infractions in Online Content Moderation
par: Samory, Mattia, et autres
Publié: (2025)

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
par: Gohar, Usman, et autres
Publié: (2024)

Fairness of ChatGPT
par: Li, Yunqi, et autres
Publié: (2023)

FairGridSearch: A Framework to Compare Fairness-Enhancing Models
par: Ma, Shih-Chi, et autres
Publié: (2024)

FairJob: A Real-World Dataset for Fairness in Online Systems
par: Vladimirova, Mariia, et autres
Publié: (2024)

SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
par: Wang, Zhihao, et autres
Publié: (2024)

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
par: Tang, Zeyu, et autres
Publié: (2025)

FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
par: Zhu, Lin, et autres
Publié: (2025)

Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
par: Zhang, Lujing, et autres
Publié: (2024)

Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages
par: Dinh, My H., et autres
Publié: (2024)

Inducing Human-like Biases in Moral Reasoning Language Models
par: Karpov, Artem, et autres
Publié: (2024)

FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
par: Cong, Zicun, et autres
Publié: (2024)

Counterfactual Fairness with Graph Uncertainty
par: Valério, Davi, et autres
Publié: (2026)

Perturbation Effects on Accuracy and Fairness among Similar Individuals
par: Li, Xuran, et autres
Publié: (2024)

FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition
par: Gala, Dalia, et autres
Publié: (2024)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
par: Sheng, Zhecheng, et autres
Publié: (2025)

Fair outputs, Biased Internals: Causal Potency and Asymmetry of Latent Bias in LLMs for High-Stakes Decisions
par: Tripathy, Jagdish, et autres
Publié: (2026)

Procedural Fairness Through Decoupling Objectionable Data Generating Components
par: Tang, Zeyu, et autres
Publié: (2023)

Large Language Models are Geographically Biased
par: Manvi, Rohin, et autres
Publié: (2024)