Federated Learning Aggregation

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Overview

Federated learning aggregation studies how to combine knowledge from clients that keep their data local, so they can train useful models together. Methods range from FedAvg-style weighted averaging to client weighting, clustering, prototypes, and personalization; newer approaches also align low-rank or function-space updates when model parameters are not directly compatible. Robust filters and trust scores address poisoned or unreliable updates, while secure, asynchronous, and over-the-air aggregation target privacy, delays, and communication costs. No single strategy works best across settings: performance depends on client heterogeneity and participation, and practical designs must trade off accuracy, fairness, security, privacy, and efficiency.

Latest papers

CardsList

270 papers38 papers in the last four weeks, up 15% on the four weeks before. 0.2% of all new papers.

  1. A Step Toward Federated Pretraining of Multimodal Large Language Models

    Mar 25, 2026Baochen Xiong, Yifan Xu, Xiaoshan Yang +3Multimodal Federated LearningMultimodal Pretraining

    MAIS, Institute of Automation, Chinese Academy of Sciences · Pengcheng Laboratory · School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS) +1

  2. Byzantine-Robust and Differentially Private Federated Optimization under Weaker Assumptions

    Mar 24, 2026Rustem Islamov, Grigory Malinovsky, Alexander Gaponov +3Byzantine-Robust Federated LearningDifferentially Private Federated Learning

    University of Basel, Switzerland · KAUST, Saudi Arabia · MBZUAI, UAE

  3. 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

  4. 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

  5. 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.

  6. TAPAS: Efficient Two-Server Asymmetric Private Aggregation Beyond Prio(+)

    Mar 20, 2026Harish Karthikeyan, Antigoni PolychroniadouSecure AggregationSecure Multi-Party Computation

    JPMorgan AI Research, JPMorgan AlgoCRYPT CoE

  7. 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.

  8. 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

  9. 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

  10. 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

  11. SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning

    Mar 16, 2026Ran Tao, Qiugang Zhan, Shantian Yang +3Federated LearningHeterogeneous Federated Learning

    Complex Laboratory of New Finance and Economics, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, China · Engineering Research Center of Intelligent Finance, Ministry of Education, China · Kash Institute of Electronics and Information Industry, China +2

  12. Federated Few-Shot Learning on Neuromorphic Hardware: An Empirical Study Across Physical Edge Nodes

    Mar 13, 2026Steven Motta, Gioele NanniFederated LearningFederated Learning Aggregation

  13. Projection Guided Personalized Federated Learning for Low Dose CT Denoising

    Mar 12, 2026Anas Zafar, Muhammad Waqas, Amgad Muneer +2LDCT DenoisingFederated Learning

    The University of Texas MD Anderson Cancer Center, Houston, TX, USA

  14. Repurposing Backdoors for Good: Ephemeral Intrinsic Proofs for Verifiable Aggregation in Cross-silo Federated Learning

    Mar 11, 2026Xian Qin, Xue Yang, Xiaohu TangFederated Learning Aggregation

    Southwest Jiaotong University

  15. Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation

    Mar 9, 2026Patrick Wilhelm, Odej KaoFederated Learning AggregationAsynchronous Federated Learning

    BIFOLD, Technische Universität Berlin, Berlin, Germany · Technische Universität Berlin, Berlin, Germany

  16. Stabilized Fine-Tuning with LoRA in Federated Learning: Mitigating the Side Effect of Client Size and Rank via the Scaling Factor

    Mar 9, 2026Jiayu Huang, Xiaohu Wu, Tiantian He +1Federated Fine-TuningLow-Rank Adaptation

    Beijing University of Posts and Telecommunications, Beijing, China · Agency for Science, Technology and Research, Singapore, Singapore

  17. FedMomentum: Preserving LoRA Training Momentum in Federated Fine-Tuning

    Mar 9, 2026Peishen Yan, Yang Hua, Hao Wang +4Federated Fine-TuningFederated Learning Aggregation

    Shanghai Jiao Tong University · Queen’s University Belfast · Stevens Institute of Technology +2

  18. FedEU: Evidential Uncertainty-Driven Federated Fine-Tuning of Vision Foundation Models for Remote Sensing Image Segmentation

    Mar 8, 2026Xiaokang Zhang, Xuran Xiong, Jianzhong Huang +1Federated Fine-TuningRemote Sensing Image Segmentation

    School of Artificial Intelligence, Wuhan University, Wuhan 430072, China · School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China · School of Computer Science, Wuhan University, Wuhan 430072, China

  19. FedARKS: Federated Aggregation via Robust and Discriminative Knowledge Selection and Integration for Person Re-identification

    Mar 6, 2026Xin Xu, Binchang Ma, Zhixi Yu +1Federated Domain GeneralizationPerson Re-Identification

    School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065 China

  20. Structure-Aware Distributed Backdoor Attacks in Federated Learning

    Mar 4, 2026Wang Jian, Shen Hong, Ke Wei +1Backdoor Attacks in Federated LearningAdversarial Perturbations

    Faculty of Applied Sciences, Macao Polytechnic University, R. de Luís Gonzaga Gomes, Macao, 999078, China · Faculty of Cyberspace Security, Software Engineering Institute of Guangzhou, No.548 Guangcong South Road, High-tech Industrial Park, Conghua Economic Development Zone, Guangzhou, 501900, China · School of Engineering and Technology, Central Queensland University, Bruce Highway, Norman Gardens, Rockhampton, Queensland, 4702, Australia +1

  21. Breaking the Prototype Bias Loop: Confidence-Aware Federated Contrastive Learning for Highly Imbalanced Clients

    Mar 3, 2026Tian-Shuang Wu, Shen-Huan Lyu, Ning Chen +4Federated LearningPrototype Learning

    Key Laboratory of Water Big Data Technology of Ministry of Water Resources, College of Computer Science and Software Engineering, Hohai University, Nanjing, China · Department of Computer Science, City University of Hong Kong, Hong Kong, China · State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China +1

  22. A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning

    Feb 28, 2026Rodrigo Tertulino, Laércio AlencarCardiovascular Risk PredictionDifferentially Private Federated Learning

    Federal Institute of Education, Science, and Technology of Rio Grande do Norte (IFRN), Natal 3030-290, RN, Brazil

  23. FedUAF: Uncertainty-Aware Fusion with Reliability-Guided Aggregation for Multimodal Federated Sentiment Analysis

    Feb 28, 2026Xianxun Zhu, Zezhong Sun, Imad Rida +4Multimodal Federated LearningMultimodal Sentiment Analysis

    Shanghai University, China · Nanyang Technological University, Singapore · Macquarie University, Australia +3

  24. 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

  25. 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

  26. 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.

  27. 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

  28. 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

  29. CQSA: Byzantine-robust Clustered Quantum Secure Aggregation in Federated Learning

    Feb 25, 2026Arnab Nath, Harsh KasyapFederated Learning AggregationByzantine-Robust Federated Learning

    Indian Institute of Technology (BHU), Varanasi, India

  30. 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)