Fairness in ML

AAAI 2024arXiv:2403.12474

#2

OpenBias: Open-set Bias Detection in Text-to-Image Generative Models

Moreno D&#x27, Incà, Elia Peruzzo et al.

FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization

Cheng Yang, Jixi Liu, Yunhe Yan et al.

graph neural networksfairness in gnnssensitive information neutralizationbias mitigation+3

33

ICLR 2024arXiv:2403.01189

#4

Training Unbiased Diffusion Models From Biased Dataset

Yeongmin Kim, Byeonghu Na, Minsang Park et al.

32

ECCV 2024arXiv:2407.08813

#5

FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification

Yu Tian, Congcong Wen, Min Shi et al.

algorithmic fairnessdomain adaptationdomain generalizationmedical image segmentation+4

26

CVPR 2024arXiv:2404.03242

#6

Would Deep Generative Models Amplify Bias in Future Models?

Tianwei Chen, Yusuke Hirota, Mayu Otani et al.

23

ICLR 2024arXiv:2310.18913

#7

Debiasing Algorithm through Model Adaptation

Tomasz Limisiewicz, David Mareček, Tomáš Musil

21

ICLR 2025arXiv:2410.19803

#8

First-Person Fairness in Chatbots

Tyna Eloundou, Alex Beutel, David Robinson et al.

chatbot fairnesscounterfactual evaluationfirst-person fairnessbias assessment+4

19

ICLR 2024arXiv:2306.07261

#9

Diversity-Aware Policy Optimization for Large Language Model Reasoning

Jian Yao, Ran Cheng, Xingyu Wu et al.

Fair-VPT: Fair Visual Prompt Tuning for Image Classification

Sungho Park, Hyeran Byun

Unprocessing Seven Years of Algorithmic Fairness

André F. Cruz, Moritz Hardt

18

ICLR 2025arXiv:2410.20247

#12

Model Equality Testing: Which Model is this API Serving?

Irena Gao, Percy Liang, Carlos Guestrin

16

AAAI 2024arXiv:2312.13306

#13

Towards Fair Graph Federated Learning via Incentive Mechanisms

12794 Chenglu Pan, Jiarong Xu, Yue Yu et al.

graph federated learningincentive mechanismsagent valuationgradient alignment+4

14

ICLR 2024arXiv:2311.18460

#14

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework

Maresa Schröder, Dennis Frauen, Stefan Feuerriegel

11

ICLR 2024arXiv:2310.05725

#15

Post-hoc bias scoring is optimal for fair classification

Wenlong Chen, Yegor Klochkov, Yang Liu

10

AAAI 2024arXiv:2312.05551

#16

Multi-Dimensional Fair Federated Learning

Cong Su, Guoxian Yu, Jun Wang et al.

federated learninggroup fairnessclient fairnessdifferential multipliers+3

9

ICLR 2024arXiv:2401.10632

#17

Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values

Hadi Hosseini, Samarth Khanna

Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach

Aoqi Zuo, yiqing li, Susan Wei et al.

8

ICLR 2024arXiv:2310.17256

#19

fairret: a Framework for Differentiable Fairness Regularization Terms

Maarten Buyl, MaryBeth Defrance, Tijl De Bie

8

algorithmic fairnessfairness surrogate functionsdemographic parityconstrained optimization+4

#20

Understanding Fairness Surrogate Functions in Algorithmic Fairness

Yong Liu, (Andrew) Zhanke Zhou, Zhicong Li et al.

ICLR 2025

7

AAAI 2025arXiv:2412.15504

#21

Mitigating Social Bias in Large Language Models: A Multi-Objective Approach Within a Multi-Agent Framework

Zhenjie Xu, Wenqing Chen, Yi Tang et al.

7

AAAI 2024arXiv:2311.00109

#22

Debiasing Multimodal Large Language Models via Noise-Aware Preference Optimization

zefeng zhang, Hengzhu Tang, Jiawei Sheng et al.

FairWASP: Fast and Optimal Fair Wasserstein Pre-processing

Zikai Xiong, Niccolo Dalmasso, Alan Mishler et al.

fairness pre-processingwasserstein distance minimizationdemographic paritymixed-integer programming+4

6

AAAI 2024arXiv:2401.11601

#24

Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data

Zhenqing Ling, Daoyuan Chen, Liuyi Yao et al.

Robust Evaluation Measures for Evaluating Social Biases in Masked Language Models

Yang Liu

social bias evaluationmasked language modelspseudo-log-likelihood scoresdistributional divergence measures+4

5

AAAI 2025arXiv:2410.08111

#26

Active Fourier Auditor for Estimating Distributional Properties of ML Models

Ayoub Ajarra, Bishwamittra Ghosh, Debabrota Basu

4

ICCV 2025arXiv:2507.10203

#27

Improving Multimodal Learning via Imbalanced Learning

Shicai Wei, Chunbo Luo, Yang Luo

multimodal learningimbalanced learningbias-variance analysisasymmetric representation learning+4

4

ICML 2025arXiv:2502.02966

#28

FACTER: Fairness-Aware Conformal Thresholding and Prompt Engineering for Enabling Fair LLM-Based Recommender Systems

Arya Fayyazi, Mehdi Kamal, Massoud Pedram

4

ICML 2025arXiv:2502.10563

#29

Accelerating Unbiased LLM Evaluation via Synthetic Feedback

Zhaoyi Zhou, Yuda Song, Andrea Zanette

ICML 2025arXiv:2502.06655

#30

Unbiased Evaluation of Large Language Models from a Causal Perspective

Meilin Chen, Jian Tian, Liang Ma et al.

ICML 2025arXiv:2410.13831

#31

The Disparate Benefits of Deep Ensembles

Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter et al.

NeurIPS 2025arXiv:2509.23639

#32

An Effective Theory of Bias Amplification

Arjun Subramonian, Samuel Bell, Levent Sagun et al.

LightFair: Towards an Efficient Alternative for Fair T2I Diffusion via Debiasing Pre-trained Text Encoders

Boyu Han, Qianqian Xu, Shilong Bao et al.

text-to-image diffusiontext encoder debiasingfairness in generationembedding distance constraint+4

AAAI 2024arXiv:2403.09383

#34

Enhancing Robust Fairness via Confusional Spectral Regularization

Gaojie Jin, Sihao Wu, Jiaxu Liu et al.

On Fairness of Unified Multimodal Large Language Model for Image Generation

Ming Liu, Hao Chen, Jindong Wang et al.

Pantypes: Diverse Representatives for Self-Explainable Models

Rune Kjærsgaard, Ahcène Boubekki, Line Clemmensen

prototypical self-explainable modelsrepresentation biasmachine learning fairnessinterpretable ai systems+2

AAAI 2024arXiv:2306.05059

#37

Reconciling Predictive and Statistical Parity: A Causal Approach

Drago Plecko, Elias Bareinboim

fair machine learningstatistical paritypredictive paritycausal decomposition+4

AAAI 2024arXiv:2312.10534

#38

Rethinking Robustness of Model Attributions

Sandesh Kamath, Sankalp Mittal, Amit Deshpande et al.

model attributionsattribution robustnessfeature attributionsadversarial training+3

AAAI 2025arXiv:2412.17523

#39

Constructing Fair Latent Space for Intersection of Fairness and Explainability

Hyungjun Joo, Hyeonggeun Han, Sehwan Kim et al.

AAAI 2024arXiv:2310.07535

#40

Fairness under Covariate Shift: Improving Fairness-Accuracy Tradeoff with Few Unlabeled Test Samples

Shreyas Havaldar, Jatin Chauhan, Karthikeyan Shanmugam et al.

covariate shiftfairness-accuracy tradeoffsensitive groupsweighted entropy objective+4

NeurIPS 2025arXiv:2507.02645

#41

Fair Deepfake Detectors Can Generalize

Harry Cheng, Ming-Hui Liu, Yangyang Guo et al.

deepfake detectiondemographic fairnesscross-domain generalizationcausal relationship analysis+4

NeurIPS 2025arXiv:2505.13122

#42

When majority rules, minority loses: bias amplification of gradient descent

François Bachoc, Jerome Bolte, Ryan Boustany et al.

bias amplificationgradient descent analysismajority-minority learningstereotypical predictors+3

NeurIPS 2025arXiv:2510.21363

#43

FairImagen: Post-Processing for Bias Mitigation in Text-to-Image Models

Zihao Fu, Ryan Brown, Shun Shao et al.

ICLR 2025arXiv:2410.04472

#44

Collapsed Language Models Promote Fairness

Jingxuan Xu, Wuyang Chen, Linyi Li et al.

language model fairnessneural collapse phenomenonbias mitigation techniquestoken representation alignment+2

AAAI 2025arXiv:2409.10395

#45

Can Private Machine Learning Be Fair?

Joseph Rance, Filip Svoboda

Reducing Leximin Fairness to Utilitarian Optimization

Eden Hartman, Yonatan Aumann, Avinatan Hassidim et al.

ICLR 2024arXiv:2403.02598

#47

Revisiting Fairness in Multitask Learning: A Performance-Driven Approach for Variance Reduction

Xiaohan Qin, Xiaoxing Wang, Junchi Yan

Pooling Image Datasets with Multiple Covariate Shift and Imbalance

Sotirios Panagiotis Chytas, Vishnu Lokhande, Vikas Singh

ICLR 2024arXiv:2403.18301

#49

Fairness on Principal Stratum: A New Perspective on Counterfactual Fairness

Haoxuan Li, Zeyu Tang, Zhichao Jiang et al.

Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives

Shrinivas Ramasubramanian, Harsh Rangwani, Sho Takemori et al.

ICML 2025arXiv:2501.15955

#51

Rethinking the Bias of Foundation Model under Long-tailed Distribution

Jiahao Chen, Bin Qin, Jiangmeng Li et al.

ICLR 2024arXiv:2312.03259

#52

Position: Current Model Licensing Practices are Dragging Us into a Quagmire of Legal Noncompliance

Moming Duan, Mingzhe Du, Rui Zhao et al.

You Get What You Give: Reciprocally Fair Federated Learning

Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.

B-score: Detecting biases in large language models using response history

An Vo, Mohammad Reza Taesiri, Daeyoung Kim et al.

f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization

Sina Baharlouei, Shivam Patel, Meisam Razaviyayn

ICML 2025arXiv:2506.13947

#56

Optimal Fair Learning Robust to Adversarial Distribution Shift

Sushant Agarwal, Amit Jayant Deshpande, Rajmohan Rajaraman et al.

The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models

Yan Liu, Yu Liu, Xiaokang Chen et al.

Meta Optimality for Demographic Parity Constrained Regression via Post-Processing

Kazuto Fukuchi

ICML 2025arXiv:2505.04796

#59

Robust ML Auditing using Prior Knowledge

Jade Garcia Bourrée, Augustin Godinot, Sayan Biswas et al.

ICML 2025arXiv:2206.03234

#60

Disparate Conditional Prediction in Multiclass Classifiers

Sivan Sabato, Eran Treister, Elad Yom-Tov

ICLR 2024arXiv:2310.18413

#61

On the Fairness ROAD: Robust Optimization for Adversarial Debiasing

Vincent Grari, Thibault Laugel, Tatsunori Hashimoto et al.

ICML 2025arXiv:2502.04313

#62

FDGen: A Fairness-Aware Graph Generation Model

Zichong Wang, Wenbin Zhang

Great Models Think Alike and this Undermines AI Oversight

Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina et al.

CVPR 2024arXiv:2402.17229

#64

FairPFN: A Tabular Foundation Model for Causal Fairness

Jake Robertson, Noah Hollmann, Samuel Gabriel Müller et al.

Preserving Fairness Generalization in Deepfake Detection

Li Lin, Xinan He, Yan Ju et al.

ICML 2024arXiv:2303.01704

#66

Feature Importance Disparities for Data Bias Investigations

Peter Chang, Leor Fishman, Seth Neel

feature importance disparitydata bias investigationprotected featuresfairness metrics+3

ICML 2024arXiv:2303.08516

#67

Fair Off-Policy Learning from Observational Data

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

fair off-policy learningalgorithmic decision-makingobservational datafairness notions+4

ICML 2024arXiv:2406.03255

#68

Deceptive Fairness Attacks on Graphs via Meta Learning

Jian Kang, Yinglong Xia, Ross Maciejewski et al.

Debiasing Attention Mechanism in Transformer without Demographics

Shenyu Lu, Yipei Wang, Xiaoqian Wang

Stable Fair Graph Representation Learning with Lipschitz Constraint

Qiang Chen, Zhongze Wu, Xiu Su et al.

On the Maximal Local Disparity of Fairness-Aware Classifiers

Jinqiu Jin, Haoxuan Li, Fuli Feng

fairness-aware classifiersdemographic paritylocal disparityfairness metrics+2

ICML 2025arXiv:2503.02870

#72

Multiaccuracy and Multicalibration via Proxy Groups

Beepul Bharti, Mary Clemens-Sewall, Paul H. Yi et al.

ICML 2025arXiv:2404.05678

#73

On the Alignment between Fairness and Accuracy: from the Perspective of Adversarial Robustness

Junyi Chai, Taeuk Jang, Jing Gao et al.

Position: Machine Learning Models Have a Supply Chain Problem

Sarah Meiklejohn, Hayden Blauzvern, Mihai Maruseac et al.

FairICP: Encouraging Equalized Odds via Inverse Conditional Permutation

Yuheng Lai, Leying Guan

ICML 2025arXiv:2502.04850

#76

Reward Modeling with Ordinal Feedback: Wisdom of the Crowd

Shang Liu, Yu Pan, Guanting Chen et al.

ENSUR: Equitable and Statistically Unbiased Recommendation

Nitin Bisht, Xiuwen Gong, Guandong Xu

Aequa: Fair Model Rewards in Collaborative Learning via Slimmable Networks

Nurbek Tastan, Samuel Horváth, Karthik Nandakumar

ICLR 2024arXiv:2309.16487

#79

Classes Are Not Equal: An Empirical Study on Image Recognition Fairness

Jiequan Cui, Beier Zhu, Xin Wen et al.

Towards Poisoning Fair Representations

Tianci Liu, Haoyu Wang, Feijie Wu et al.

ICLR 2024arXiv:2310.11401

#81

Enhancing Group Fairness in Online Settings Using Oblique Decision Forests

Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami et al.

CVPR 2024arXiv:2404.09454

#82

FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis

Raman Dutt, Ondrej Bohdal, Sotirios Tsaftaris et al.

Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition

Faisal Hamman, Sanghamitra Dutta

Utility-Fairness Trade-Offs and How to Find Them

Sepehr Dehdashtian, Bashir Sadeghi, Vishnu Naresh Boddeti

ICLR 2024arXiv:2403.15593

#85

Empirical Likelihood for Fair Classification

Pangpang Liu, Yichuan Zhao

Causal Logistic Bandits with Counterfactual Fairness Constraints

Jiajun Chen, Jin Tian, Chris Quinn

FairerCLIP: Debiasing CLIP's Zero-Shot Predictions using Functions in RKHSs

Sepehr Dehdashtian, Lan Wang, Vishnu Boddeti

ICML 2024arXiv:2402.03839

#88

Random features models: a way to study the success of naive imputation

Alexis Ayme, Claire Boyer, Aymeric Dieuleveut et al.

missing data imputationrandom features modelshigh-dimensional linear predictorsmissing completely at random+4

ICLR 2024arXiv:2306.09468

#89

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods

Xiaotian Han, Jianfeng Chi, Yu Chen et al.

ICLR 2024arXiv:2311.02189

#90

FairSeg: A Large-Scale Medical Image Segmentation Dataset for Fairness Learning Using Segment Anything Model with Fair Error-Bound Scaling

Yu Tian, Min Shi, Yan Luo et al.

ICLR 2024arXiv:2405.00588

#91

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra et al.

Are Models Biased on Text without Gender-related Language?

Catarina Belém, Preethi Seshadri, Yasaman Razeghi et al.

ICLR 2024arXiv:2310.06205

#93

Fair Classifiers that Abstain without Harm

Tongxin Yin, Jean-Francois Ton, Ruocheng Guo et al.

ICML 2024arXiv:2403.06812

#94

Monotone Individual Fairness

Yahav Bechavod

individual fairnessonline learningfairness violationsmonotone aggregation functions+4

fairness measurescontinuous risk scoreswasserstein distancegroup disparities+2

#95

Standardized Interpretable Fairness Measures for Continuous Risk Scores

Ann-Kristin Becker, Oana Dumitrasc, Klaus Broelemann

ICML 2024

ICML 2025arXiv:2502.00619

#96

Understanding the Unfairness in Network Quantization

Bing Liu, wenjun Miao, Boyu Zhang et al.

DAFA: Distance-Aware Fair Adversarial Training

Hyungyu Lee, Saehyung Lee, Hyemi Jang et al.

Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs

Yinong O Wang, Nivedha Sivakumar, Falaah Arif Khan et al.

Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective

Yujin Oh, Pengfei Jin, Sangjoon Park et al.

#100

Debiased Collaborative Filtering with Kernel-Based Causal Balancing

Haoxuan Li, Chunyuan Zheng, Yanghao Xiao et al.

ICLR 2024