Federated Learning

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Overview

Federated learning studies how multiple devices or institutions can train models collaboratively while keeping data local, for example across hospitals, phones, or companies. A common approach, FedAvg, aggregates local model updates; related methods use personalization or client clustering, split learning, model compression, and lightweight adapters such as LoRA. Differential privacy and secure aggregation can limit exposure of updates, while robust aggregation and client-selection methods address malicious participants and uneven data or resources. The central challenge is balancing accuracy and fairness across heterogeneous clients with privacy, security, communication cost, and reliable evaluation; keeping data local alone does not guarantee privacy or strong performance.

Latest papers

CardsList

961 papers112 papers in the last four weeks, up 1% on the four weeks before. 0.6% of all new papers.

  1. PoiCGAN: A Targeted Poisoning Based on Feature-Label Joint Perturbation in Federated Learning

    Mar 24, 2026Tao Liu, Jiguang Lv, Dapeng Man +7Data Poisoning AttacksAdversarial Attacks

    College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China

  2. Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication

    Mar 24, 2026Chen Shang, Dinh Thai Hoang, Diep N. Nguyen +1Federated LearningBrain-Computer Interfaces

    School of Electrical and Data Engineering, University of Technology Sydney, Australia · Thrust of Internet of Things, The Hong Kong University of Science and Technology (Guangzhou), China

  3. A Theoretical Framework for Energy-Aware Gradient Pruning in Federated Learning

    Mar 23, 2026Emmanouil M. AthanasakosFederated LearningEnergy-Efficient ML

    National and Kapodistrian University of Athens, Department of Informatics and Telecommunications, Athens, Greece

  4. OmniFM: Toward Modality-Robust and Task-Agnostic Federated Learning for Heterogeneous Medical Imaging

    Mar 23, 2026Meilin Liu, Jiaying Wang, Jing ShanFederated LearningHeterogeneous Federated Learning

    School of Software, Shenyang University of Technology

  5. TrustFed: Enabling Trustworthy Medical AI under Data Privacy Constraints

    Mar 23, 2026Vagish Kumar, Syed Bahauddin Alam, Souvik ChakrabortyFederated LearningUncertainty Quantification

    Department of Applied Mechanics Indian Institute of Technology Delhi · Grainger College of Engineering Nuclear, Plasma & Radiological Engineering Department National Center for Supercomputing Applications, Urbana, IL, USA · Department of Applied Mechanics Yardi School of Artificial Intelligence (ScAI) Grainger College of Engineering Indian Institute of Technology Delhi University of Illinois Urbana-Champaign, Urbana, IL, USA

  6. FedCVU: Federated Learning for Cross-View Video Understanding

    Mar 23, 2026Shenghan Zhang, Run Ling, Ke Cao +2Federated LearningVideo Understanding

    Software College, Northeastern University, Shenyang, China · University of Science and Technology of China, Hefei, China · University of Chinese Academy of Sciences, Beijing, China +1

  7. In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis

    Mar 23, 2026Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj Pokhrel +2IoT Intrusion DetectionNetwork Intrusion Detection

    School of IT, Deakin University, Geelong, Australia · School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India

  8. Modeling Quantum Federated Autoencoder for Anomaly Detection in IoT Networks

    Mar 23, 2026Devashish Chaudhary, Sutharshan Rajasegarar, Shiva Raj PokhrelQuantum Federated LearningAnomaly Detection

    School of Information Technology, Deakin University, Geelong, Australia

  9. Federated Mixture-of-Experts Alignment on Mobile Edge Networks under Data Heterogeneity

    Mar 22, 2026Zihan Fang, Qianru Wang, Haonan An +4Mixture-of-Experts Language ModelsFederated Learning Aggregation

    Hong Kong JC STEM Lab of Smart City and Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong SAR, China · School of Computer Science and Technology, Xidian University, Xi’an, China · Department of Electrical and Computer Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong, China +1

  10. Incentive-Aware Federated Averaging with Performance Guarantees under Strategic Participation

    Mar 21, 2026Fateme Maleki, Krishnan Raghavan, Farzad YousefianIncentive Mechanisms for Federated LearningFederated Learning

    Department of Industrial and Systems Engineering, Rutgers University, USA. · Argonne National Laboratory, Lemont, IL, USA.

  11. Federated Hyperdimensional Computing for Resource-Constrained Industrial IoT

    Mar 20, 2026Nikita Zeulin, Olga Galinina, Nageen Himayat +1Industrial Internet of ThingsHyperdimensional Computing

    Tampere University, Tampere, Finland · Tampere Institute for Advanced Study, Tampere University, Finland · Intel Corporation, Santa Clara, CA, United States

  12. Low-pass Personalized Subgraph Federated Recommendation

    Mar 20, 2026Wooseok Sim, Hogun ParkPopularity Bias in Recommender SystemsRecommender Systems

    Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea

  13. FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients

    Mar 20, 2026Tian Wen, Zhiqin Yang, Yonggang Zhang +4Federated LearningLearning with Noisy Labels

    Institute of Computing Technology, Chinese Academy of Sciences · TMLR Group, Hong Kong Baptist University · The Hong Kong University of Science and Technology +1

  14. A Locally Penalized Cross-Estimate Federated Method with Guarantees for Constrained Personalized Learning

    Mar 20, 2026Mohammadjavad Ebrahimi, Daniel Burbano, Farzad YousefianFederated LearningHeterogeneous Federated Learning

    Department of Industrial and Systems Engineering, Rutgers University, USA. · Department of Electrical and Computer Engineering, Rutgers University, USA.

  15. ARMOR: Adaptive Resilience Against Model Poisoning Attacks in Continual Federated Learning for Mobile Indoor Localization

    Mar 20, 2026Danish Gufran, Akhil Singampalli, Sudeep PasrichaFederated LearningFederated Continual Learning

    Colorado State University, Fort Collins, CO 80523, USA

  16. Scalable Cross-Facility Federated Learning for Scientific Foundation Models on Multiple Supercomputers

    Mar 20, 2026Yijiang Li, Zilinghan Li, Kyle Chard +4Federated LearningHeterogeneous Federated Learning

    Mathematics and Computer Science Division, Argonne National Laboratory · Data Science and Learning Division, Argonne National Laboratory · Department of Computer Science, University of Chicago

  17. FedAgain: A Trust-Based and Robust Federated Learning Strategy for an Automated Kidney Stone Identification in Ureteroscopy

    Mar 19, 2026Ivan Reyes-Amezcua, Francisco Lopez-Tiro, Clément Larose +3Trust-Aware Federated LearningFederated Learning

    Centro de Investigación y de Estudios Avanzados del IPN (CINVESTAV), Departamento de Ciencias Computacionales, Guadalajara, 45017, Jalisco, Mexico · Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, 64849, N.L., Mexico · CRAN UMR 7039, Université de Lorraine and CNRS, Vandœuvre-lès-Nancy, France +1

  18. FedTrident: Resilient Road Condition Classification Against Poisoning Attacks in Federated Learning

    Mar 19, 2026Sheng Liu, Panos PapadimitratosFederated LearningClient Selection in Federated Learning

    Networked Systems Security Group, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden

  19. Communication-Efficient and Robust Multi-Modal Federated Learning via Latent-Space Consensus

    Mar 19, 2026Mohamed Badi, Chaouki Ben Issaid, Mehdi BennisMultimodal Federated LearningFederated Learning

    Center for Wireless Communications, University of Oulu, Oulu 90014, Finland

  20. When Differential Privacy Meets Wireless Federated Learning: An Improved Analysis for Privacy and Convergence

    Mar 19, 2026Chen Yaoling, Liang Hao, Tu XiaotongDifferentially Private Federated LearningFederated Learning

    School of Informatics, Xiamen University, China · Internet of Things Thrust, Hong Kong University of Science and Technology (Guangzhou), China

  21. DriftGuard: Mitigating Asynchronous Data Drift in Federated Learning

    Mar 19, 2026Yizhou Han, Di Wu, Blesson VargheseFederated LearningFederated Continual Learning

    School of Computer Science, University of St Andrews, UK

  22. Revisiting Label Inference Attacks in Vertical Federated Learning: Why They Are Vulnerable and How to Defend

    Mar 19, 2026Yige Liu, Dexuan Xu, Zimai Guo +2Federated Learning

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education; School of Computer Science, Peking University, Beijing, China. · Zhongguancun Laboratory, Beijing, China.

  23. Beyond Passive Aggregation: Active Auditing and Topology-Aware Defense in Decentralized Federated Learning

    Mar 19, 2026Sheng Pan, Niansheng TangFederated LearningBackdoor Attacks in Federated Learning

    Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming 650091, China

  24. ARES: Scalable and Practical Gradient Inversion Attack in Federated Learning through Activation Recovery

    Mar 18, 2026Zirui Gong, Leo Yu Zhang, Yanjun Zhang +4Gradient Inversion AttacksFederated Learning

    Griffith University · Swinburne University of Technology · City University of Macau +1

  25. QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation

    Mar 18, 2026Charuka Herath, Yogachandran Rahulamathavan, Varuna De Silva +1Federated LearningNeural Network Quantization

    Institute of Digital Technologies, Loughborough University, UK

  26. Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization

    Mar 18, 2026Ratun Rahman, Dinh C. NguyenFederated LearningHeterogeneous Federated Learning

    Department of Electrical and Computer Engineering, University of Alabama in Huntsville, Huntsville, AL 35899, USA

  27. FastPFRec: A Fast Personalized Federated Recommendation with Secure Sharing

    Mar 18, 2026Zhenxing Yan, Jidong Yuan, Yongqi Sun +2Recommender SystemsFederated Learning

    Key Laboratory of Big Data & Artificial Intelligence in Transportation (Beijing Jiaotong University), Ministry of Education, Beijing, 100044, China · School of Computer Science and Technology, Beijing Jiaotong University, Beijing, 100044, China

  28. Dynamic Meta-Layer Aggregation for Byzantine-Robust Federated Learning

    Mar 17, 2026Reek Das, Biplab Kanti SenByzantine-Robust Federated LearningFederated Learning Aggregation

    APC Roy Government College · Assistant Professor, Department of Computer Science P.R. Thakur Government College

  29. Federated Learning with Multi-Partner OneFlorida+ Consortium Data for Predicting Major Postoperative Complications

    Mar 17, 2026Yuanfang Ren, Varun Sai Vemuri, Zhenhong Hu +6Clinical Risk PredictionClinical Outcome Prediction

    Intelligent Clinical Care Center, University of Florida, Gainesville, FL. · Department of Medicine, Division of Nephrology, Hypertension, and Renal Transplantation, University of Florida, Gainesville, FL. · Department of Surgery, University of Florida, Gainesville, FL. +1

  30. FederatedFactory: Generative One-Shot Learning for Extremely Non-IID Distributed Scenarios

    Mar 17, 2026Andrea Moleri, Christian Internò, Ali Raza +4Federated LearningNon-IID Federated Learning

    Honda Research Institute Europe, Germany · University of Milan-Bicocca, Italy · Bielefeld University, Germany +1