Algorithmic Fairness

Follow this topic Ask about this topic

Momentum

29 papers in the last four weeks, up 71% on the four weeks before. 0.3% of all new papers.

Jul 13Week of Sep 28

Latest papers 275

All topics

Identification and Inference for Algorithmic Frontiers with Selective Labels
Jun 12, 2026Yiqi Liu, Francesca Molinari, Amilcar VelezDebiased ML Parameter Identifiability
Department of Economics, Cornell University
α-Fair Insurance Pricing: A Fairness Continuum
Jun 12, 2026Tianhe Zhang, Xiguang Liu, Peng ShiAlgorithmic Fairness Group Fairness
Department of Risk and Insurance, Wisconsin School of Business, University of Wisconsin–Madison · Department of Information Systems and Operations Management, Warrington College of Business, University of Florida
Disparate Impact in Synthetic Data Generation
Jun 11, 2026Paul Andrey, Michaël Perrot, Batiste Le Bars +1Synthetic Data Generation Algorithmic Fairness
Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189 - CRIStal, F-59000 Lille, France
$α$ -fair heterogeneous agent reinforcement learning
Jun 11, 2026Yao-hua Franck Xu, Tayeb Lemlouma, Jean-Marie Bonnin +1Algorithmic Fairness Policy Optimization
Orange Innov Lannion, France · IRISA Université de Rennes Lannion, France · IRISA IMT Atlantique Rennes, France
Towards Provably Fair Machine Learning: Bayesian Approaches For Consistent and Transparent Predictions
Jun 10, 2026Owen O'Neill, Fintan CostelloSelective Prediction Bayesian Inference
University College Dublin, Ireland
Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles
Jun 10, 2026Shun Shao, Zheng Zhao, Anna Korhonen +2Debiased ML Algorithmic Fairness
University of Cambridge · University of Edinburgh · University of Groningen +1
Towards Fully Automated Exam Grading: Fairness-Aware Recognition of Handwritten Answers with Foundation Models
Jun 9, 2026Hartwig GrabowskiVLM Evaluation Algorithmic Fairness
Institute for Machine Learning and Analytics (IMLA), Offenburg University, Offenburg, Germany.
Ethical and Technical Limits of Deepfake Speech Datasets
Jun 9, 2026Vojtěch Staněk, Eva Trnovská, Kamil Malinka +1Data Leakage Audio Deepfake Detection
Is Fairness Truly Fair? Towards Reliable Lipschitz Fairness in Multi-Task Learning via Fixed-\texorpdfstring{ $δ$ }{delta} Alignment
Jun 9, 2026Junbo Ding, Xin Zang, Chenchen Pan +3Algorithmic Fairness Multi-Task Learning
Beijing University of Chemical Technology Beijing, China
Trading Utility for Dynamic Fairness in Multiple Resource Division with Sequential Demand
Jun 9, 2026Kaiqi Jiang, Karim El Husseini, Wenzhe Fan +1Sequential Decision Making Fair Resource Allocation
Computer Science Dept., University of Illinois Chicago, Chicago, Illinois, USA
PAFO: Pareto Fairness Optimization for Personalized Reward Modeling
Jun 6, 2026Xiaoyan Zhao, Haoting Ni, Yang Zhang +3Reward Modeling LLM Alignment
National University of Singapore · University of Science and Technology of China · Peking University
Be Fair! Can Machine Learning Engineering Agents Adhere to Fairness Constraints?
Jun 3, 2026Anna Richter, Julia Stoyanovich, Sebastian SchelterAlgorithmic Fairness AI Agent Evaluation
BIFOLD & TU Berlin · New York University
UniFair: A unified fair clustering approach based on separation and compactness
Jun 3, 2026Antonia Karra, Vasiliki Papanikou, Georgios Vardakas +2Clustering Algorithmic Fairness
University of Ioannina, Greece · Archimedes/Athena Research Center, Greece
Toward Calibrated, Fair, and accurate Deepfake Detection
Jun 3, 2026Ryan Brown, Chris RussellAlgorithmic Fairness Deepfake Detection
University of Oxford
Adaptive Calibration for Fair and Performant Facial Recognition
Jun 3, 2026Ryan Brown, Chris RussellPost-Hoc Calibration Algorithmic Fairness
University of Oxford
Detecting and Mitigating Bias by Treating Fairness as a Symmetry Operation
Jun 2, 2026Nishit SinghDebiased ML Algorithmic Fairness
Birla Institute of Technology and Science, Pilani.
Fairness Definitions and Metrics in Deep Reinforcement Learning for Drug Discovery in Healthcare: A Rapid Evidence Review
Jun 1, 2026Esmaeil Shakeri, Ronnie de Souza Santos, Behrouz FarReinforcement Learning Algorithmic Fairness
Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Canada
The Crowded Embedding Space: A Mean-Field Mechanism for Emergent Marginalization in Retrieval-Augmented Agents
Jun 1, 2026Shwan Ashrafi, Dan RothAlgorithmic Fairness Mean-Field Theory
Oracle AI
FairGen: Preference-Aligned Diffusion for Demographically Equitable Medical Image Synthesis
Jun 1, 2026Zhimin Li, Ruichen Zhang, Zhen Tan +3Diffusion Model Alignment Synthetic Data Augmentation
University of Pittsburgh, Swanson School of Engineering, Pittsburgh, 15261, USA · 2The University of North Carolina at Chapel Hill, Department of Computer Science, Chapel Hill, 27599, USA · 3Arizona State University, School of Computing and Augmented Intelligence, Tempe, 85281, USA +1
Model Multiplicity and Predictive Arbitrariness in Recidivism Risk Assessment
Jun 1, 2026Ashwin Singh, Carlos CastilloAlgorithmic Fairness
TU Wien, Vienna, Austria · ICREA and Universitat Pompeu Fabra, Barcelona, Spain
TriAlign: Towards Universal Truth Consistency in Personalized LLM Alignment
Jun 1, 2026Thi-Nhung Nguyen, Linhao Luo, Rollin Omari +3LLM Alignment Algorithmic Fairness
Department of Data Science & AI, Monash University · Defence Science and Technology Group, Australia
Fair Finetuning Mitigates Distribution Inference Attacks
Jun 1, 2026Rakshit NaiduData Leakage Algorithmic Fairness
Georgia Institute of Technology
KG-FairDiff: Knowledge Graph-Guided Prompt Refinement for Demographically Fair Text-to-Image Generation
May 31, 2026Farbod Davoodi, Seyed Reza Tavakoli Shiyadeh, Pooria Safaei +12T2I Generation Algorithmic Fairness
Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar
Fairness in two-player zero-sum games with bandit feedback
May 31, 2026S Akash, Pratik GajaneNash Equilibrium Zero-Sum Games
LatentForce.ai Bengaluru, India · Laboratoire d’Informatique Fondamentale d’Orléans University of Orléans, France
Silent Failures in Federated Personalization of Foundation Models
May 31, 2026YongKyung Oh, Alex BuiAlgorithmic Fairness Privacy-Preserving ML
Medical & Imaging Informatics (MII) Group, University of California, Los Angeles (UCLA) Los Angeles, CA, 90024, USA
Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation
May 30, 2026Xinpeng Lv, Chunyuan Zheng, Yunxin Mao +9Strategic Classification Algorithmic Fairness
College of Computer Science and Technology, National University of Defense Technology · Institute for Theoretical Computer Science, Shanghai University of Finance and Economics · School of Mathematical Sciences, Peking University +3
Partial Fairness Awareness: Belief-Guided Strategic Mechanism for Strategic Agents
May 30, 2026Xinpeng Lv, Chunyuan Zheng, Yunxin Mao +8Strategic Classification Mechanism Design
National University of Defense Technology, Changsha, China · Peking University, Beijing, China · Shanghai University of Finance and Economics, Shanghai, China +2
COPF: An Online Framework for Deployment-Stable Counterfactual Fairness in Evolving Graphs
May 30, 2026Sheng'en Li, Dongmian ZouAlgorithmic Fairness Counterfactual Fairness
Zu Chongzhi Center and DIRC, Duke Kunshan University, Kunshan, China.
Demystifying the Optimal Fair Classifier in Multi-Class Classification
May 30, 2026Li Zhang, Yuyuan Li, XiaoHua Feng +3Algorithmic Fairness Group Fairness
College of Computer Science and Technology, Zhejiang University · School of Communication Engineering, Hangzhou Dianzi University
Shortcuts in the Tail: Debiasing via Post-Hoc Spectral Compression of Fine-Tuning Updates
May 29, 2026Edward Sun, Dmitrii TroitskiiLLM Fine-Tuning Algorithmic Fairness
Department of Computer Science, UCLA, Los Angeles, CA, USA · Independent.

Jun 12, 2026, econ.EMJ/K move · Enter open · S save

Identification and Inference for Algorithmic Frontiers with Selective Labels

Yiqi Liu, Francesca Molinari, Amilcar Velez

Department of Economics, Cornell University

Debiased ML Parameter Identifiability Algorithmic Fairness Partial Identification Causal Identifiability Selective Labels

Open paper AskPDF arXiv

This paper provides identification results to characterize a fairness-accuracy (FA) frontier, and statistical inference tools to test hypotheses and build a confidence set for the FA-frontier, when outcomes are observed only for selected individuals. When the selection process is unrestricted but loss is measured in specific ways, we provide a characterization of the sharp identification region of the FA-frontier. Under an assumption of unconfoundedness conditional on observables (and unrestricted loss functions), we obtain point identification and propose a debiased machine learning estimator, derive its asymptotic distribution, and show how this can be used to carry out inference for the FA-frontier. In work in progress, we extend the partial identification results to a broader class of loss functions.

Momentum

Related topics

Latest papers 275