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. EdgeFLow: Serverless Federated Learning via Sequential Model Migration in Edge Networks

    Mar 3, 2026Yuchen Shi, Qijun Hou, Pingyi Fan +1Federated LearningCommunication-Efficient Distributed Training

    Dept. of Electronic Engineering, BNRist, Tsinghua University. · Dept. of Electronic and Computer Engineering, HKUST.

  2. CA-AFP: Cluster-Aware Adaptive Federated Pruning

    Mar 2, 2026Om Govind Jha, Harsh Shukla, Haroon R. LoneFederated LearningNeural Network Pruning

    IISER Bhopal Bhopal, India

  3. Decentralized Federated Learning by Partial Message Exchange

    Mar 2, 2026Shan Sha, Shenglong Zhou, Xin Wang +2Communication-Efficient Distributed TrainingFederated Learning

    School of Mathematics and Statistics, Beijing Jiaotong University, Beijing, China. · Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, U.K.

  4. Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting

    Mar 2, 2026Yi Li, Han Liu, Mingfeng Fan +3Federated LearningFederated Graph Learning

    School of Automation, Central South University · Department of Electrical and Computer Engineering, National University of Singapore · Department of Mechanical Engineering, National University of Singapore +2

  5. Fed-ADE: Adaptive Learning Rate for Federated Post-adaptation under Distribution Shift

    Mar 1, 2026Heewon Park, Mugon Joe, Miru Kim +2Adaptive Learning RateFederated Learning

    Department of Electrical and Computer Engineering, Sungkyunkwan University, Republic of Korea · Soongsil University, Seoul, Republic of Korea

  6. DeepAFL: Deep Analytic Federated Learning

    Feb 28, 2026Jianheng Tang, Yajiang Huang, Kejia Fan +8Gradient-Free OptimizationFederated Learning

    Peking University, PRC · Key Lab of High Confidence Software Technologies (PKU), Ministry of Education, PRC · Central South University, PRC +4

  7. FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning

    Feb 27, 2026Jieming Bian, Lei Wang, Letian Zhang +1Federated Fine-TuningFederated Learning

    University of Florida, Gainesville, FL 32611 · Middle Tennessee State University Murfreesboro, TN 37132

  8. Trust Aware Federated Learning for Secure Bone Healing Stage Interpretation in e-Health

    Feb 27, 2026Paul Shepherd, Tasos Dagiuklas, Bugra Alkan +2Trust-Aware Federated LearningFederated Learning

    London South Bank University, London, UK · Instituto de Telecomunica¸c˜oes, Aveiro, Portugal

  9. FedNSAM:Consistency of Local and Global Flatness for Federated Learning

    Feb 27, 2026Junkang Liu, Fanhua Shang, Yuxuan Tian +2Federated LearningSharpness-Aware Minimization

    College of Intelligence and Computing, Tianjin University, Tianjin, China · College of Management and Economics, Tianjin University, Tianjin, China · Medical College, Tianjin University; Peng Cheng Laboratory, Tianjin, China +1

  10. FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA

    Feb 27, 2026Haoran Zhang, Dongjun Kim, Seohyeon Cha +1Federated Fine-TuningFederated Learning

    Chandra Department of Electrical and Computer Engineering, The University of Texas at Austin, TX, USA.

  11. FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments

    Feb 26, 2026Anik Pramanik, Murat Kantarcioglu, Vincent Oria +1Clustered Federated LearningFederated Learning

    New Jersey Institute of Technology, USA · Virginia Tech, USA

  12. SettleFL: Trustless and Scalable Reward Settlement Protocol for Federated Learning on Permissionless Blockchains (Extended version)

    Feb 26, 2026Shuang Liang, Yang Hua, Linshan Jiang +4Incentive Mechanisms for Federated LearningBlockchain-Based Federated Learning

    Shanghai Jiao Tong University · Queen's University Belfast · Queen’s University Belfast +1

  13. Beyond performance-wise Contribution Evaluation in Federated Learning

    Feb 25, 2026Balazs PejoFederated Learning

    CrySyS Lab, Hungary

  14. Learning to Collaborate via Structures: Cluster-Guided Item Alignment for Federated Recommendation

    Feb 25, 2026Yuchun Tu, Zhiwei Li, Bingli Sun +2Recommender SystemsFederated Learning

    Beihang University, Beijing, China · University of Technology Sydney, Sydney, Australia · University of Edinburgh, Edinburgh, UK

  15. GFPL: Generative Federated Prototype Learning for Resource-Constrained and Data-Imbalanced Vision Task

    Feb 25, 2026Shiwei Lu, Yuhang He, Jiashuo Li +2Federated LearningFederated Learning Aggregation

    Xi’an Jiaotong University · Air Force Engineering University

  16. JSAM: Privacy Straggler-Resilient Joint Client Selection and Incentive Mechanism Design in Differentially Private Federated Learning

    Feb 25, 2026Ruichen Xu, Ying-Jun Angela Zhang, Jianwei HuangIncentive Mechanisms for Federated LearningClient Selection in Federated Learning

    Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong · School of Science and Engineering, Shenzhen Institute of Artificial Intelligence and Robotics for Society, Shenzhen Key Laboratory of Crowd Intelligence Empowered Low-Carbon Energy Network, and CSIJRI Joint Research Centre on Smart Energy Storage, The Chinese University of Hong Kong, Shenzhen, Guangdong, 518172, P.R. China

  17. Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning

    Feb 25, 2026Mario García-Márquez, Nuria Rodríguez-Barroso, M. Victoria Luzón +1Blockchain-Based Federated LearningFederated Learning

    Department of Computer Science and Artificial Intelligence, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Granada · Department of Software Engineering, Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI) University of Granada Granada

  18. Private and Robust Contribution Evaluation in Federated Learning

    Feb 25, 2026Delio Jaramillo Velez, Gergely Biczok, Alexandre Graell i Amat +2Federated LearningPrivacy-Preserving ML

    University of La Laguna Tenerife, Spain · HUN-REN Hungarian Research Network Budapest, Hungary · Chalmers University Gotheburg, Sweden +2

  19. FedVG: Gradient-Guided Aggregation for Enhanced Federated Learning

    Feb 24, 2026Alina Devkota, Jacob Thrasher, Donald Adjeroh +2Federated LearningFederated Learning Aggregation

    West Virginia University · University of Aberdeen · Fogsphere (Redev.AI)

  20. ProxyFL: A Proxy-Guided Framework for Federated Semi-Supervised Learning

    Feb 24, 2026Duowen Chen, Yan WangFederated LearningHeterogeneous Federated Learning

    Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University

  21. Benchmarking Federated Learning in Edge Computing Environments: A Systematic Review and Performance Evaluation

    Feb 24, 2026Sales Aribe, Gil Nicholas CagandeFederated LearningCommunication-Efficient Distributed Training

    Information Technology Department, Bukidnon State University, Malaybalay City, Philippines

  22. On Electric Vehicle Energy Demand Forecasting and the Effect of Federated Learning

    Feb 24, 2026Andreas Tritsarolis, Gil Sampaio, Nikos Pelekis +1Electricity Load ForecastingFederated Learning

    Department of Informatics, University of Piraeus, Piraeus, Greece · Center for Power and Energy Systems, INESC TEC, Porto, Portugal · Department of Statistics and Insurance Science, University of Piraeus, Piraeus, Greece

  23. Federated Learning for Cross-Modality Medical Image Segmentation via Augmentation-Driven Generalization

    Feb 24, 2026Sachin Dudda Nagaraju, Ashkan Moradi, Bendik Skarre Abrahamsen +1Cross-Modality Medical Image SegmentationData Augmentation

    Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway. · Central Staff, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.

  24. Bikelution: Federated Gradient-Boosting for Scalable Shared Micro-Mobility Demand Forecasting

    Feb 24, 2026Antonios Tziorvas, Andreas Tritsarolis, Yannis TheodoridisSpatiotemporal ForecastingFederated Learning

    Department of Informatics, University of Piraeus, Piraeus, Greece

  25. Is the Trigger Essential? A Feature-Based Triggerless Backdoor Attack in Vertical Federated Learning

    Feb 24, 2026Yige Liu, Yiwei Lou, Che Wang +2Backdoor AttacksBackdoor Attacks in Federated 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.

  26. Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA

    Feb 24, 2026Nuocheng Yang, Sihua Wang, Ouwen Huan +3Federated Fine-TuningFederated Learning

    Beijing Laboratory of Advanced Information Network, and the Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China · Department of Electrical and Computer Engineering and Institute for Data Science and Computing, University of Miami, Coral Gables, FL, 33146 USA · Information Systems Technology and Design Pillar, Singapore University of Technology and Design, 487372, Singapore

  27. A Secure and Private Distributed Bayesian Federated Learning Design

    Feb 23, 2026Nuocheng Yang, Sihua Wang, Zhaohui Yang +3Federated LearningDecentralized Learning

    Beijing Laboratory of Advanced Information Network, and the Beijing Key Laboratory of Network System Architecture and Convergence, Beijing University of Posts and Telecommunications, Beijing 100876, China · College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China, and Zhejiang Provincial Key Lab of Information Processing, Communication and Networking (IPCAN), Hangzhou 310007, China · Department of Electrical and Computer Engineering and Institute for Data Science and Computing, University of Miami, Coral Gables, FL, 33146 USA +1

  28. DP-FedAdamW: An Efficient Optimizer for Differentially Private Federated Large Models

    Feb 23, 2026Jin Liu, Yinbin Miao, Ning Xi +1Differentially Private Federated LearningFederated Learning

    School of Cyber Engineering, Xidian University, Xi’an, China · College of Intelligence and Computing, Tianjin University, Tianjin, China

  29. Personalized Longitudinal Medical Report Generation via Temporally-Aware Federated Adaptation

    Feb 23, 2026He Zhu, Ren Togo, Takahiro Ogawa +8Medical Report GenerationFederated Learning

    Hokkaido University

  30. Federated Learning Playground

    Feb 23, 2026Bryan Shan, Alysa Ziying Tan, Han YuFederated Learning

    Nanyang Technological University (NTU), Singapore · Alibaba-NTU Singapore Joint Research Institute, NTU, Singapore · Alibaba Group, Hangzhou, China