Group Fairness

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14 papers in the last four weeks, up 250% on the four weeks before. 0.1% of all new papers.

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Latest papers 98

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Multigroup Fairness and Omniprediction: Separations and Equivalences
Oct 5, 2026Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade +3Group Fairness Multicalibration
Stanford University · Apple · University of Oxford +2
FairProp: Fair Node Representation Learning via Differentiable Propagation Layers
Oct 5, 2026Emmanouil Kariotakis, Aritra KonarGraph Neural Networks Graph Representation Learning
Department of Electrical Engineering (ESAT-STADIUS), KU Leuven, Belgium
Groupwise Distortion Guarantees for Preference-Based Alignment
Oct 4, 2026Jacob Brodkey, Roberto Tamez, Aaron RothPairwise Preference Learning Social Choice Theory
University of Pennsylvania
Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening
Oct 1, 2026Jie Tang, Chuanlong Xie, Lixing ZhuAlgorithmic Auditing Algorithmic Fairness
School of Statistics, Beijing Normal University, Zhuhai, Guangdong 519087, China
Efficient Active Auditing of Multi-Group Fairness with Bias Probes
Sep 30, 2026Ayoub Ajarra, Debabrota BasuAlgorithmic Fairness Group Fairness
´Equipe Scool, Univ. Lille, Inria, CNRS, Centrale Lille, UMR 9189- CRIStAL
Fairness Theatre: Evaluating Post-Hoc Fairness Interventions in Vendor-Controlled Early Warning Systems
Sep 29, 2026Kelly McConvey, Angelina Zhai, Rebecca Li +1Algorithmic Auditing Algorithmic Fairness
University of Toronto, Toronto, Ontario, Canada · Georgia Institute of Technology, Atlanta, Georgia, USA
A Comprehensive View of Fairness through Distributional Stability
Sep 29, 2026Gayane Taturyan, Charlotte Laclau, Stephan ClémenconDistribution Shift Robustness Algorithmic Fairness
LTCI, Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France
Investigating the Effect of k-NN Preprocessing on Developing Graph Neural Networks: A Fairness-Based Perspective
Sep 27, 2026Nikolaos Zafeiropoulos, Emmanouil Mavrikos, George E. TsekourasGraph Neural Networks Algorithmic Fairness
Department of Cultural Technology and Communication University of the Aegean Mytilene, Greece
When Post-Processing Fairness Constraints Help and When They Harm: Evidence from Eight Cross-Domain Evaluations
Sep 22, 2026Nithin Raghava Ramachandra NarlaAlgorithmic Auditing Algorithmic Fairness
Independent Researcher, Dallas-Fort Worth, Texas, United States
Multi-View Fair Clustering Guided by Cross-View Sensitive Information Discrepancy
Sep 22, 2026Mudi Jiang, Jiahui Zhou, Xinying Liu +2Multi-View Learning Unsupervised Clustering
School of Software, Dalian University of Technology, Dalian, Liaoning, China
Identifying Representational Biases in Datasets Using PCA: A Max-Disparity Partition Framework
Sep 21, 2026Arjun KM, Shashi JainPrincipal Component Analysis Algorithmic Fairness
Department of Management Studies Indian Institute of Science, Bangalore
The AR Fairness Metamodel: A Structured Framework for Fairness Measures
Sep 16, 2026Julian Alfredo Mendez, Timotheus KampikFair Resource Allocation Algorithmic Fairness
Umeå University, Umeå, Sweden
Fed-Equilibrium Framework for Topological Pareto Control in Robust and Fair Clinical Federated Learning
Sep 14, 2026Ting Xu, Henry LeungFederated Learning Aggregation Byzantine-Robust Federated Learning
Department of Biomedical Engineering University of Calgary Calgary, Canada
Evaluating Model Retraining under Drift: Paired Comparisons of Cumulative Subgroup Disparity
Sep 9, 2026Aaron CerossAlgorithmic Fairness Group Fairness
Birmingham Law School, University of Birmingham
A Sub-4 Approximation for Fair $k$ -Means
Sep 7, 2026Kangke Cheng, Guanlin Mo, Shihong Song +1Clustering Group Fairness
University of Science and Technology of China, Hefei, China · School of Informatics, University of Edinburgh, Edinburgh, UK
Prevalence calibration as shortcut mitigation
Sep 7, 2026Mohamed Amine Kina, Eike PetersenPost-Hoc Calibration Medical Image Classification
Universität Bremen, Bremen, Germany · Fraunhofer Institute for Digital Medicine MEVIS, Bremen, Germany
Bias Mitigation in Face Recognition via Demographic-based Supervised Contrastive Learning
Aug 13, 2026Yu Linghu, Salman Mohammad, Xinyi Zhang +1Algorithmic Fairness Group Fairness
Department of Informatics University of Zurich
Group Alignment-Induced Sycophancy: A Two-Sided Evaluation of Steerable Pluralistic Alignment
Aug 12, 2026Haokai Zhao, Yunze Xiao, Weihao Xuan +3LLM Sycophancy LLM Alignment
University of New South Wales · Carnegie Mellon University · University of Tokyo
Procedural Fairness Failures in RLHF from Preference Averaging
Aug 10, 2026M P V S Gopinadh, Karthik Kamuju, Kummari Avinash +2Reward Modeling Algorithmic Fairness
Vishnu Institute of Technology
Fairness in Link Prediction Beyond Demographic Parity: A Reproducibility Study
Aug 10, 2026Valentijn Oldenburg, Floris de Kam, Stef de Wildt +1Learning to Rank Link Prediction
University of Amsterdam
Learning Long-Term Educational Investment Policies under Residential Sorting
Aug 7, 2026Honglei Guo, Shuo Chen, Mingjie Bi +3Group Fairness
College of Artificial Intelligence, Zhejiang University · State Key Laboratory of General Artificial Intelligence, BIGAI
Fairis: Fairness-Aware Aggregation with Provable Influence Containment against Fairness Poisoning Attacks in Collaborative Machine Learning
Aug 6, 2026Devharsh Trivedi, Nesrine Kaaniche, Nikos Triandopoulos +2Federated Learning Aggregation Byzantine-Robust Federated Learning
Department of Computer Science, Bowie State University, MD, USA · SAMOVAR, T´el´ecom SudParis, Institut Polytechnique de Paris, Palaiseau, France · Department of Computer Science, Brown University, RI, USA +1
Variable Selection in the Context of AI Fairness
Aug 4, 2026Ivan Luciano Danesi, Chiara Frigerio, Fabio Maccaferri +2Algorithmic Fairness Group Fairness
UniCredit S.p.A., Milan, Italy. · 2Universit`a Cattolica del Sacro Cuore, Milan, Italy. · 3Cetif, Milan, Italy.
Fairness Auditing: Lower Bounds on Company Manipulation
Aug 1, 2026Rachit Verma, Padala Manisha, Sujit GujarAlgorithmic Auditing Algorithmic Fairness
Indian Institute of Technology Gandhinagar · International Institute of Information Technology Hyderabad
End-to-End Fairness Optimization with Fair Decision-Focused Learning
Jul 31, 2026Yu Wang, Violet Xinying ChenFair Resource Allocation Algorithmic Fairness
School of Business Stevens Institute of Technology
Parameterized Fair Resource Allocation under Diversity Constraints
Jul 29, 2026Keke Huang, Yik Yu Ng, Laks V. S. Lakshmanan +1Fair Resource Allocation Group Fairness
Huazhong University of Science and Technology Wuhan, Hubei, China · The University of British Columbia Vancouver, BC, Canada · McGill University Montreal, Quebec, Canada +1
Outcome-Fair Restless Multi-Armed Bandits for Stochastic Deadline Scheduling
Jul 26, 2026Shakti Sharma, Rahul MeshramSequential Decision Making Fair Resource Allocation
Dept. of Physics, IIT Madras, Chennai, India. · Dept. of Electrical Engineering, IIT Madras, Chennai, India.
Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors
Jul 24, 2026Ibne Farabi Shihab, Joyanta Jyoti Mondal, Anuj SharmaMulti-Armed Bandits Fair Resource Allocation
Department of Computer Science, Iowa State University, USA · Department of Computer and Information Sciences, University of Delaware, USA · Department of Civil, Construction & Environmental Engineering, Iowa State University, USA
COVAriance-Induced Fairness Gap Penalty for Subgroup-Fair Clustering
Jul 20, 2026Kyungseon Lee, Hankyo Jeong, Kunwoong Kim +2Clustering Algorithmic Fairness
Department of Statistics, Seoul National University · KAIST AI
The Optimization Trilemma: Efficiency, Comfort and Fairness in Decentralized Multi-agent Coordination
Jul 19, 2026Jovan Nikolic, Maciej Krzysztof Zuziak, Evangelos PournarasMulti-Agent Coordination Fair Resource Allocation
Google, Zurich, 8002 Zurich, Switzerland. · School of Computer Science, University of Leeds, Leeds, UK. · School of Energy Systems, LUT University, 53850 Lappeenranta, Finland

Oct 5, 2026, cs.LGJ/K move · Enter open · S save

Multigroup Fairness and Omniprediction: Separations and Equivalences

Sílvia Casacuberta, Parikshit Gopalan, Varun Kanade, Omer Reingold+2

Stanford University · Apple · University of Oxford+2

Group Fairness Multicalibration

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Omniprediction is a learning guarantee which requires a single predictor to be competitive relative to the best hypothesis from a benchmark class for any loss chosen from a family of loss functions. Loss Outcome Indistinguishability (loss OI for short) is a stronger notion that implies omniprediction. It requires the predicted distribution on labels to be indistinguishable from the true distribution to tests that depend on the loss functions and the benchmark class. Multiaccuracy and multicalibration are multigroup fairness notions that generalize classical notions of calibration and accuracy in expectation. Most known learning algorithms for omniprediction (both for the standard notion and for strengthenings like loss OI) rely on some version of these multigroup fairness notions, or on an intermediate notion called calibrated multiaccuracy. We ask if this is necessary: Does omniprediction require some form of multigroup fairness? We show that the answer is no for (plain) omniprediction, and yes for loss OI. First, a sequence of works shows that multicalibration or calibrated multiaccuracy imply omniprediction. We rule out even a weak converse, by showing that omniprediction for proper losses does not imply even accuracy in expectation, a much weaker notion than any of calibration, multiaccuracy, or multicalibration. Second, prior work showed how to achieve loss OI from a combination of calibration and multiaccuracy. We show a converse: loss OI is equivalent to a form of calibrated multiaccuracy.

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