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. Optimizing Stochastic Gradient Push under Broadcast Communications

    Apr 16, 2026Tuan Nguyen, Ting HeCommunication-Efficient Distributed TrainingFederated Learning

    Pennsylvania State University State College, PA, USA

  2. No More Guessing: a Verifiable Gradient Inversion Attack in Federated Learning

    Apr 16, 2026Francesco Diana, Chuan Xu, André Nusser +1Gradient Inversion AttacksAdversarial Attacks

    Université Côte d’Azur, France · Inria, France · CNRS, France +1

  3. FedGUI: Benchmarking Federated GUI Agents across Heterogeneous Platforms, Devices, and Operating Systems

    Apr 16, 2026Wenhao Wang, Haoting Shi, Mengying Yuan +7Benchmark DesignGUI Agents

    Zhejiang University · Shanghai Jiao Tong University · Multi-Agent Governance & Intelligence Crew (MAGIC) +2

  4. Cooperate to Compete: Strategic Data Generation and Incentivization Framework for Coopetitive Cross-Silo Federated Learning

    Apr 16, 2026Thanh Linh Nguyen, Nguyen Van Huynh, Quoc-Viet PhamSynthetic Data GenerationPotential Games

    School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, D02 PN40, Ireland · School of Computer Science and Informatics, University of Liverpool, Liverpool, L69 3DR, UK

  5. Exploiting Correlations in Federated Learning: Opportunities and Practical Limitations

    Apr 16, 2026Adrian Edin, Michel Kieffer, Mikael Johansson +1Communication-Efficient Distributed TrainingGradient Compression

    Department of Electrical Engineering (ISY), Linköping University, SE-581 83 Linköping, Sweden · CentraleSupélec, CNRS, L2S, Université Paris-Saclay, Gif-sur-Yvette, FR-91192, France · Division of Decision and Control Systems, School of EECS, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden

  6. Asynchronous Probability Ensembling for Federated Disaster Detection

    Apr 15, 2026Emanuel Teixeira Martins, Rodrigo Moreira, Larissa Ferreira Rodrigues Moreira +3Federated LearningAsynchronous Federated Learning

    Federal University of Espirito Santo (UFES), Vitória-ES, Brazil · Federal University of Rio Grande do Norte (UFRN), Natal-RN, Brazil · University of Minho (UMinho), Braga, Portugal

  7. On-Orbit Space AI: Federated, Multi-Agent, and Collaborative Algorithms for Satellite Constellations

    Apr 15, 2026Ziyang WangMulti-Agent CoordinationDistributed Inference

  8. Secure and Privacy-Preserving Vertical Federated Learning

    Apr 15, 2026Shan Jin, Sai Rahul Rachuri, Yizhen Wang +2Privacy-Preserving Federated LearningFederated Learning

    Visa Research

  9. Rethinking the Personalized Relaxed Initialization in the Federated Learning: Consistency and Generalization

    Apr 14, 2026Li Shen, Yan Sun, Dacheng TaoFederated LearningNon-IID Federated Learning

    School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University · School of Computer Science, Faculty of Engineering, The University of Sydney · Generative AI Lab, College of Computing and Data Science, Nanyang Technological University

  10. The Impact of Federated Learning on Distributed Remote Sensing Archives

    Apr 13, 2026Anand Umashankar, Karam Tomotaki-Dawoud, Nicolai SchneiderFederated LearningNon-IID Federated Learning

    Technische Universität Berlin Berlin, Germany

  11. Representation-Aligned Multi-Scale Personalization for Federated Learning

    Apr 13, 2026Wenfei Liang, Wee Peng TayFederated LearningHeterogeneous Federated Learning

    Department of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.

  12. A Full Compression Pipeline for Green Federated Learning in Communication-Constrained Environments

    Apr 13, 2026Elouan Colybes, Shirin Salehi, Anke SchmeinkFederated LearningCommunication-Efficient Distributed Training

    Chair of Information Theory and Data Analytics (INDA), RWTH Aachen University, Aachen, Germany

  13. Task2vec Readiness: Diagnostics for Federated Learning from Pre-Training Embeddings

    Apr 12, 2026Cristiano Mafuz, Rodrigo SilvaFederated LearningHeterogeneous Federated Learning

  14. Communication-Efficient Gluon in Federated Learning

    Apr 12, 2026Xun Qian, Alexander Gaponov, Grigory Malinovsky +1Communication-Efficient Distributed TrainingFederated Learning

    Center of Excellence for Generative AI, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.

  15. FedRio: Personalized Federated Social Bot Detection via Cooperative Reinforced Contrastive Adversarial Distillation

    Apr 12, 2026Yingguang Yang, Hao Liu, Xin Zhang +8Social Bot DetectionFederated Learning

    School of Cyber science at University of Science and Technology of China, Hefei 230026, China · State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China · Institute of Data Science at the National University of Singapore, 119077, Singapore +4

  16. Energy-Efficient Federated Edge Learning For Small-Scale Datasets in Large IoT Networks

    Apr 12, 2026Haihui Xie, Wenkun Wen, Shuwu Chen +2Federated LearningEnergy-Efficient ML

    College of Computer and Information Sciences, Fujian Agriculture and Forestry University, and also with the Engineering Research Center of Smart Sensing and Agricultural Chip Technology, Fujian Province University, Fuzhou 350002, China · R&D Department, Techphant Technologies Company Ltd., Guangzhou 510310, China · School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou 510006, China

  17. Enhancing Cross-Problem Vehicle Routing via Federated Learning

    Apr 12, 2026Xiangchi Meng, Jianan Zhou, Jie Gao +4Vehicle RoutingNeural Combinatorial Optimization

    Dalian University of Technology · Nanyang Technological University · Delft University of Technology +1

  18. FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning

    Apr 12, 2026Tao Liu, Xuehe WangIncentive Mechanisms for Federated LearningFederated Learning

    School of Artificial Intelligence, Sun Yat-sen University, Zhuhai 519082, China

  19. XFED: Non-Collusive Model Poisoning Attack Against Byzantine-Robust Federated Classifiers

    Apr 10, 2026Israt Jahan Mouri, Muhammad Ridowan, Muhammad Abdullah AdnanFederated LearningByzantine-Robust Federated Learning

    Bangladesh University of Engineering and Technology (BUET), Dhaka, Bangladesh · TigerIT Bangladesh Ltd., Dhaka, Bangladesh

  20. Prototype-Regularized Federated Learning for Cross-Domain Aspect Sentiment Triplet Extraction

    Apr 10, 2026Zongming Cai, Jianhang Tang, Zhenyong Zhang +3Aspect-Based Sentiment AnalysisFederated Learning

    State Key Laboratory of Public Big Data, Guizhou University · College of Computer Science and Technology, Guizhou University · School of Information Engineering, Guangdong University of Technology +1

  21. Quantization Impact on the Accuracy and Communication Efficiency Trade-off in Federated Learning for Aerospace Predictive Maintenance

    Apr 9, 2026Abdelkarim LoukiliGradient QuantizationFederated Learning

  22. PrivFedTalk: Privacy-Aware Federated Diffusion with Identity-Stable Adapters for Personalized Talking-Head Generation

    Apr 9, 2026Soumya Mazumdar, Vineet Kumar Rakesh, Tapas SamantaTalking Head GenerationFederated Learning

    Department of Computer Science and Business Systems Gargi Memorial Institute of Technology Affiliated to Maulana Abul Kalam Azad University of Technology Balarampur, Mouza Beralia, Baruipur, Kolkata 700144, West Bengal, India · Engineering Sciences, Homi Bhabha National Institute Anushaktinagar, Mumbai, Maharashtra 400094, India · Computer and Informatics Group / Radioactive Ion Beam Facilities Group Variable Energy Cyclotron Centre 1/AF, Bidhannagar, Kolkata 700064, West Bengal, India

  23. FedDetox: Robust Federated SLM Alignment via On-Device Data Sanitization

    Apr 8, 2026Shunan Zhu, Jiawei Chen, Yonghao Yu +1LLM Safety AlignmentFederated Learning

    The University of Tokyo, Tokyo, Japan

  24. FedDAP: Domain-Aware Prototype Learning for Federated Learning under Domain Shift

    Apr 8, 2026Huy Q. Le, Loc X. Nguyen, Yu Qiao +3Federated LearningDistribution Shift

    G-LAMP NEXUS Institute, Kyung Hee University · Kyung Hee University

  25. SubFLOT: Submodel Extraction for Efficient and Personalized Federated Learning via Optimal Transport

    Apr 8, 2026Zheng Jiang, Nan He, Yiming Chen +1Federated LearningHeterogeneous Federated Learning

    Tsinghua University · Beijing University of Technology · Key Laboratory of Pervasive Computing, Ministry of Education

  26. FedSpy-LLM: Towards Scalable and Generalizable Data Reconstruction Attacks from Gradients on LLMs

    Apr 7, 2026Syed Irfan Ali Meerza, Feiyi Wang, Jian LiuGradient Inversion AttacksPrivacy Leakage in Language Models

    University of Tennessee, Knoxville, TN, USA · Oak Ridge National Laboratory, Oak Ridge, USA · University of Georgia, Athens, GA, USA

  27. Scalar Federated Learning for Linear Quadratic Regulator

    Apr 6, 2026Mohammadreza Rostami, Shahriar Talebi, Solmaz S. KiaFederated LearningLinear Quadratic Regulator

    University of California, Irvine, CA, US · University of California, Los Angeles, CA, US

  28. Agentic Federated Learning: The Future of Distributed Training Orchestration

    Apr 6, 2026Rafael O. Jarczewski, Gabriel U. Talasso, Leandro Villas +1Federated LearningClient Selection in Federated Learning

    Institute of Computing, University of Campinas and Hub of Artificial Intelligence and Cognitive Architectures - H.IAAC, Campinas, Brazil

  29. Dynamic Free-Rider Detection in Cross-Silo Federated Learning via Simulated Attack Patterns

    Apr 6, 2026Motoki NakamuraFederated Learning

    Fujitsu Limited, Kanagawa, Japan

  30. Discrete Prototypical Memories for Federated Time Series Foundation Models

    Apr 6, 2026Liwei Deng, Qingxiang Liu, Xinhe Niu +5Time-Series Foundation ModelsFederated Learning

    Australian Artificial Intelligence Institute, University of Technology Sydney · The Hong Kong University of Science and Technology (Guangzhou) · Shenzhen University +2