Algorithmic Fairness

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

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Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification
Jul 4, 2026Ha-Hieu Pham, Hai-Dang Nguyen, Dang P. M. Cao +5Long-Tailed Classification Chest X-Ray Classification
University of Science, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam · VinUni-Illinois Smart Health Center, VinUniversity, Hanoi, Vietnam +3
CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness
Jul 1, 2026Xinyu Jia, Weidong Guo, Wangyuan Zhao +3Algorithmic Fairness Medical Image Synthesis
College of Biomedical Engineering, Fudan University, Shanghai, China
WIDER-FAIR: An Annotated Version of the WIDER-FACE Dataset for Fairness Evaluation
Jun 30, 2026Maxime Moussi, Benoît Ronval, Siegfried Nijssen +1Algorithmic Fairness Algorithmic Bias
UCLouvain, Louvain-la-Neuve, Belgium · UCLouvain, ICTEAM, Louvain-la-Neuve, Belgium · UCLouvain, ICTEAM, Louvain-la-Neuve, Belgium and KU Leuven, DTAI, Leuven, Belgium +1
Sequential Fairness Auditing with Limited Output Access
Jun 29, 2026Ioannis Pitsiorlas, Martha V. Sourla, Marios KountourisAlgorithmic Fairness Group Fairness
EURECOM, France · DaSCI, University of Granada, Spain
Accelerometry-Derived Digital Biomarkers for Cardiometabolic Risk: A Population-Representative Tabular Benchmark with Uncertainty Quantification
Jun 29, 2026Federico FelizziAlgorithmic Fairness Wearable Health Monitoring
SIIAM, Rome, Italy · enGene Statistics, Basel, Switzerland.
Fairness Attacks on Recommender Systems
Jun 27, 2026Yanan Wang, Yong GeAdversarial Attacks Algorithmic Fairness
Department of Information Systems and Operations Management, College of Business, The University of Texas at Arlington · Department of Management Information Systems, Eller College of Management, the University of Arizona
Can LLMs Hire Fairly? Racial Bias in Resume Screening
Jun 27, 2026Zhenyu Gao, Wenxi Jiang, Yutong YanGender Bias in Language Models Social Bias in Language Models
Department of Finance, CUHK Business School, The Chinese University of Hong Kong
Reproducing FACTER: Fairness via Conformal Thresholding and Prompt Repair
Jun 26, 2026Oscar Miró López-Feliu, Daimy van Loo, Xanthos Kekkos +2Algorithmic Fairness Conformal Prediction
University of Amsterdam
Fair Classification with Efficient and Post-hoc Controllable Fairness-Accuracy Trade-off
Jun 26, 2026Maaya Sakata, Kazuto FukuchiAlgorithmic Fairness
University of Tsukuba, Japan · 2RIKEN AIP, Japan
Productionized Fairness Measurement Under Privacy Constraints
Jun 25, 2026Osonde A. Osoba, Yuzi He, Saikrishna Badrinarayanan +3Algorithmic Fairness Privacy-Preserving ML
LinkedIn, California, USA
Prompt Injection in Automated Résumé Screening with Large Language Models: Single and Multi-Injection Settings
Jun 25, 2026Preet Baxi, Jiannan Xu, Jane Yi Jiang +1Algorithmic Fairness Prompt Injection Attacks
Department of Physics, University of Michigan · Robert H. Smith School of Business, University of Maryland · Fisher College of Business, The Ohio State University +1
Scoring Is Not Enough: Addressing Gaps in Utility-fairness Trade-offs for Ranking
Jun 24, 2026Shubham Singh, Ian A. Kash, Mesrob I. OhannessianLearning to Rank Algorithmic Fairness
Department of Computer Science University of Illinois Chicago Chicago, IL 60607 · Department of Electrical and Computer Engineering University of Illinois Chicago Chicago, IL 60607
Statistical and Structural Approaches to Algorithmic Fairness
Jun 24, 2026Antonio FerraraAlgorithmic Auditing Algorithmic Fairness
Graz University of Technology · Institute of Human-Centred Computing · Graz
BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases
Jun 23, 2026Qi Chen, Wenxuan Li, Pedro R. A. S. Bassi +14Distribution Shift Medical Image Analysis
Johns Hopkins University · German Cancer Research Center · University Hospital Basel +10
Dual-Branch Cross-Projection Debiasing through Diffusion-based Disentanglement
Jun 23, 2026Xiangqian Zhao, Xinyang Jiang, Zhipeng Xu +5Disentangled Representation Learning Debiased ML
Xidian University · Shaanxi, China · Microsoft Research Asia +1
Breaking the Filter Bubble: A Semantic Pareto-DQN Framework for Multi-Objective Recommendation
Jun 23, 2026Cláudio Lúcio Do Val Lopes, Lucca Machado da Silva, André de Oliveira BrandãoMulti-Objective Reinforcement Learning Algorithmic Fairness
A3Data - MG, Brazil
FairBED: A Bayesian Experimental Design Approach to Gathering Fairer Data
Jun 22, 2026Marcel Hedman, Emily Alger, Brieuc Lehmann +2Algorithmic Fairness Bayesian Experimental Design
Department of Statistics University of Oxford · Department of Statistical Science University College London
The Unseen Hand: Manipulating Model Fairness and SHAP with Targeted Identity Re-Association Attacks
Jun 22, 2026Sannaan Khan, Muhammad U. S. KhanAdversarial Attacks Algorithmic Fairness
National University of AbstractSciences and Technology (NUST)
The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders
Jun 20, 2026Weiqin Yang, Yue Pan, Chongming Gao +4Spectral Regularization Sequential Recommendation
Zhejiang University · State Key Laboratory of Blockchain and Data Security, Zhejiang University · College of Computer Science and Technology, Zhejiang University +2
Data Bias Mitigation under Coverage Constraints & The Price of Fairness
Jun 18, 2026Bruno Scarone, Alfredo Viola, Renée J. MillerDebiased ML Algorithmic Fairness
Khoury College of Computer Sciences, Northeastern University, USA · Casa de Investigadores Científicos La Comarca, Uruguay · Cheriton School of Computer Science, University of Waterloo, Canada
The Algorithmic-Human Manager: AI, Apps, and Workers in the Indian Gig Economy
Jun 18, 2026Omir Kumar, Krishnan NarayananAlgorithmic Fairness AI Governance
Policy Analyst, Centre for Responsible AI, IIT Madras (CeRAI) · Researcher, CeRAI, IIT Madras · Co-founder and President, itihaasa Research and Digital
Fair Online Resource Allocation
Jun 17, 2026Christopher En, Yuri Faenza, Andrea Lodi +1Sequential Decision Making Fair Resource Allocation
Columbia University, IEOR Department · Cornell Tech · Universidad de Chile
Fair Cognitive Impairment Detection Through Unlearning
Jun 17, 2026William Nguyen, Jiali Cheng, Hadi AmiriAdversarial Representation Learning Algorithmic Fairness
University of Massachusetts Lowell, USA
Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks
Jun 16, 2026Ngela Landon Ntung, Floride Tuyisenge, Jema David NdibwileVision Transformer Algorithmic Fairness
College of Engineering, Carnegie Mellon University Africa, Kigali, Rwanda
Learning Fair Pareto-Optimal Policies in Multi-Objective Reinforcement Learning
Jun 16, 2026Umer Siddique, Peilang Li, Yongcan CaoMulti-Objective Reinforcement Learning Algorithmic Fairness
Department of Electrical and Computer Engineering, University of Texas at San Antonio
FairTutor: Equity-Aware Pedagogical LLM Routing for Budget-Constrained AI Tutoring
Jun 16, 2026Qingyang XuIntelligent Tutoring Systems AI in Education
Independent researcher, Shanghai, China
No-Free-Fairness: Fundamental Limits and Trade-offs in Learning Systems
Jun 16, 2026Khoat ThanAlgorithmic Fairness Group Fairness
Hanoi University of Science and Technology
Geometrical fairness in graph neural networks
Jun 16, 2026Arturo Pérez-Peralta, Sandra Benítez-Peña, Blas Kolic +1Graph Neural Networks Graph Representation Learning
Department of Statistics, University Carlos III of Madrid, Spain · uc3m-Santander Big Data Institute
AgentFairBench: Do LLM Agents Discriminate When They Act?
Jun 15, 2026Triveni Morla, Rohith Reddy Bellibaltu, Manpreet Singh +1Algorithmic Fairness LLM Agent Evaluation
Florida International University, Miami, FL 33199 USA · Boston University, Boston, MA 02215 USA · Department of Computer Science and Engineering, Indian Institute of Technology Patna, Patna, Bihar, India
Repeated Bilateral Trade: The Quest for Fairness
Jun 13, 2026François Bachoc, Roberto Colomboni, Emilie KaufmannMechanism Design Algorithmic Fairness
University of Lille Institut Universitaire de France (IUF) Lille, France · School of Mathematics University of Bristol Fry Building, Woodland Road Bristol BS8 1UG, United Kingdom · Univ. Lille, CNRS, Inria, Centrale Lille, UMR 9189-CRIStAL F-59000 Lille, France

Jul 4, 2026, cs.LGJ/K move · Enter open · S save

Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification

Ha-Hieu Pham, Hai-Dang Nguyen, Dang P. M. Cao, Thanh-Huy Nguyen+4

University of Science, Ho Chi Minh City, Vietnam · Vietnam National University, Ho Chi Minh City, Vietnam · VinUni-Illinois Smart Health Center, VinUniversity, Hanoi, Vietnam+3

Long-Tailed Classification Chest X-Ray Classification Algorithmic Fairness Group Fairness

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In chest X-ray (CXR) classification, acceptable ranking performance can still leave rare-positive patients below threshold, especially within subgroups. We study this pre-deployment fairness problem as an audit question: after a long-tailed multi-label CXR model is converted from scores into decisions, who is missed? Across VinDr-CXR and MIMIC-CXR/CXR-LT, we use a diagnostic ladder to separate class-level long-tail losses, subgroup-aware weighting, group robustness, and threshold selection. On VinDr-CXR, group-tail weighting followed by tail-aware thresholding reduces tail FNR from 0.665 to 0.269, sex worst-group FNR from 0.705 to 0.157, and age worst-group FNR from 0.822 to 0.133, while macro-mAP increases from 0.611 to 0.635. On MIMIC-CXR/CXR-LT, the same score-to-threshold comparison reduces tail FNR from 0.866 to 0.741 and lowers worst-group FNR across sex, age, race, and insurance; residual missed-positive rates nevertheless remain high. Paired bootstrap contrasts on VinDr support the thresholded FNR reductions, and GroupDRO reference runs indicate that aggregate group robustness alone does not remove rare subgroup misses in this setting. The study supports a narrow audit claim: rare-label fairness in CXR depends jointly on the finding, subgroup, and operating threshold, not on label frequency or ranking metrics alone.

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