Cover Image

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

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Yi, Lu, Dongyuan, Sang, Jitao
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Backdoor for Debias: Mitigating Model Bias with Backdoor Attack-based Artificial Bias
by: Wu, Shangxi, et al.
Published: (2023)

Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)

FairDD: Fair Dataset Distillation
by: Zhou, Qihang, et al.
Published: (2024)

TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
by: Qiu, Xiangfei, et al.
Published: (2024)

A Post-Processing-Based Fair Federated Learning Framework
by: Zhou, Yi, et al.
Published: (2025)

FairPOT: Balancing AUC Performance and Fairness with Proportional Optimal Transport
by: Liu, Pengxi, et al.
Published: (2025)

Procedural Fairness via Group Counterfactual Explanation
by: Popoola, Gideon, et al.
Published: (2026)

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

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
by: Han, Xiaotian, et al.
Published: (2023)

Multi-Output Distributional Fairness via Post-Processing
by: Li, Gang, et al.
Published: (2024)

Fairness in Federated Learning: Fairness for Whom?
by: Taik, Afaf, et al.
Published: (2025)

Learning Aggregation Rules in Participatory Budgeting: A Data-Driven Approach
by: Fairstein, Roy, et al.
Published: (2024)

Data Augmentation via Diffusion Model to Enhance AI Fairness
by: Blow, Christina Hastings, et al.
Published: (2024)

BaBE: Enhancing Fairness via Estimation of Latent Explaining Variables
by: Binkyte, Ruta, et al.
Published: (2023)

OxonFair: A Flexible Toolkit for Algorithmic Fairness
by: Delaney, Eoin, et al.
Published: (2024)

FairPFN: Transformers Can do Counterfactual Fairness
by: Robertson, Jake, et al.
Published: (2024)

FairMT: Fairness for Heterogeneous Multi-Task Learning
by: Hu, Guanyu, et al.
Published: (2025)

Fair CCA for Fair Representation Learning: An ADNI Study
by: Hou, Bojian, et al.
Published: (2025)

AI Biases as Asymmetries: A Review to Guide Practice
by: Waters, Gabriella, et al.
Published: (2025)

Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making
by: Alamdari, Parand A., et al.
Published: (2023)

Fair Text-to-Image Diffusion via Fair Mapping
by: Li, Jia, et al.
Published: (2023)

Asking For It: Question-Answering for Predicting Rule Infractions in Online Content Moderation
by: Samory, Mattia, et al.
Published: (2025)

Long-Term Fairness Inquiries and Pursuits in Machine Learning: A Survey of Notions, Methods, and Challenges
by: Gohar, Usman, et al.
Published: (2024)

Fairness of ChatGPT
by: Li, Yunqi, et al.
Published: (2023)

FairGridSearch: A Framework to Compare Fairness-Enhancing Models
by: Ma, Shih-Chi, et al.
Published: (2024)

FairJob: A Real-World Dataset for Fairness in Online Systems
by: Vladimirova, Mariia, et al.
Published: (2024)

SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models
by: Wang, Zhihao, et al.
Published: (2024)

Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
by: Tang, Zeyu, et al.
Published: (2025)

FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
by: Zhu, Lin, et al.
Published: (2025)

Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks
by: Zhang, Lujing, et al.
Published: (2024)

Learning Fair Ranking Policies via Differentiable Optimization of Ordered Weighted Averages
by: Dinh, My H., et al.
Published: (2024)

Inducing Human-like Biases in Moral Reasoning Language Models
by: Karpov, Artem, et al.
Published: (2024)

FairSample: Training Fair and Accurate Graph Convolutional Neural Networks Efficiently
by: Cong, Zicun, et al.
Published: (2024)

Counterfactual Fairness with Graph Uncertainty
by: Valério, Davi, et al.
Published: (2026)

Perturbation Effects on Accuracy and Fairness among Similar Individuals
by: Li, Xuran, et al.
Published: (2024)

FairTargetSim: An Interactive Simulator for Understanding and Explaining the Fairness Effects of Target Variable Definition
by: Gala, Dalia, et al.
Published: (2024)

Toward Unifying Group Fairness Evaluation from a Sparsity Perspective
by: Sheng, Zhecheng, et al.
Published: (2025)

Fair outputs, Biased Internals: Causal Potency and Asymmetry of Latent Bias in LLMs for High-Stakes Decisions
by: Tripathy, Jagdish, et al.
Published: (2026)

Procedural Fairness Through Decoupling Objectionable Data Generating Components
by: Tang, Zeyu, et al.
Published: (2023)

Large Language Models are Geographically Biased
by: Manvi, Rohin, et al.
Published: (2024)