Latest Federated Learning Research Papers
The newest Federated Learning papers from across the field — arXiv, NeurIPS, CVPR, Nature, and more — refreshed daily and ranked by relevance. Distill AI tracks Federated Learning so you don’t have to: get the standout work delivered to your inbox every morning, with 2-sentence summaries and the option to chat with any paper.
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- Contribution-based Federated Learning in CybersecurityDhruv Sharma, Deepti Agrawal, Kulraj Singh · Journal of the Association ... · Aug 15, 2026
Cybersecurity attacks impose operational, financial, and reputational harm to organizations, yet information sharing remains limited due to competitive and disclosure concerns. We propose Federated Learning (FL) as a solution, using a game-…
- Future Directions in Artificial IntelligenceSunil Kumar · Zenodo (CERN European Organ... · Aug 9, 2026
Artificial Intelligence (AI) is rapidly evolving beyond narrow applications toward transparent, ethical, and generalized systems. As AI increasingly impacts critical sectors, the research focus is shifting from mere computational accuracy t…
- Future Directions in Artificial IntelligenceSunil Kumar · Zenodo (CERN European Organ... · Aug 9, 2026
Artificial Intelligence (AI) is rapidly evolving beyond narrow applications toward transparent, ethical, and generalized systems. As AI increasingly impacts critical sectors, the research focus is shifting from mere computational accuracy t…
- Recent Advances in Artificial Intelligence for Health CareBhagyajyothi S. Kannur · Zenodo (CERN European Organ... · Aug 9, 2026
Artificial intelligence (AI) has rapidly become a transformative force in health care, enhancing diagnostic accuracy, treatment planning, patient monitoring, and operational efficiency. This article explores advanced and emerging AI techniq…
- Recent Advances in Artificial Intelligence for Health CareBhagyajyothi S. Kannur · Zenodo (CERN European Organ... · Aug 9, 2026
Artificial intelligence (AI) has rapidly become a transformative force in health care, enhancing diagnostic accuracy, treatment planning, patient monitoring, and operational efficiency. This article explores advanced and emerging AI techniq…
- Strategic analysis of players in satellite federated learning service market: A tripartite evolutionary game modelManxia Cao, Qi Wang, Qi Wang, Qi Wang et al. · Engineering Applications of... · Jul 22, 2026
- AMLNet: A Decentralised Anti-Money Laundering Detection Framework Using Federated Learning, Blockchain, and Zero-Knowledge ProofsPriya S, Dakshayini M, Apsana S A, Anjana M R · Zenodo (CERN European Organ... · Jul 22, 2026
One of these financial crimes, which seem to sound like a concept straight out of a dream until you get a sense of the magnitude of the issue, is money laundering. According to the United Nations, Between $800 billion and $2 trillion in ill…
- DRFAS-enhanced personalized federated learning for secure and robust cardiovascular disease detectionV.Karthik, Omkumar Chandraumakantham, Sudhakaran Gajendran, Suguna Marappan · Scientific Reports · Jul 22, 2026
The integration of privacy protection in smart healthcare systems has revolutionized disease detection and patient monitoring, but privacy concerns arise from the collection and analysis of sensitive health data. Federated learning (FL) off…
- Quantum fed-ARIS: quantum-enhanced federated continual learning for autonomous RIS-UAV constellation networks with digital twin-guided predictive optimizationJ. Girish, Jitendra Kumar, V. Premalatha · Life Cycle Reliability and ... · Jul 22, 2026
- Privacy-Preserving Audio-Visual Speech Separation with Asymmetric Federated Split LearningVasiliki Mavridou, Panagiotis Sidiropoulos, Theodoros Lappas · OpenAlex · Jul 21, 2026
- Enhancing Tomato Leaf Disease Detection Using Federated Learning for Efficiency and Privacy PreservationOns Loukil, Slim Amri, Walid Barhoumi · Vietnam Journal of Computer... · Jul 21, 2026
Tomato cultivation is vital for global food security, yet it faces considerable challenges from foliar diseases that can profoundly reduce crop yields. Early and real-time detection of these diseases is essential to maintain agricultural pr…
- Privacy-Aware Federated Capsule Network with Flash Attention for Robust Spatial Mammogram Analysis and Cancer DetectionNirmala Venkatachalam, Sathish Kumar Kannaiah, R. Prabavathi, S. Vinodh Kumar · Figshare · Jul 20, 2026
Globally, breast cancer is considered as a major cause of cancer related illness and death among women. Hence, it requires an early and precise diagnosis system to lower the mortality rate. The conventional deep learning models pose privacy…
- A Fairness Perspective on Client Selection and Aggregation Methods for Non-IID Mitigation in Federated Learning: A SurveyMohannad Alsofyani, Isra Al-Turaiki, Hassan Mathkour · Electronics · Jul 20, 2026
Federated learning (FL) is a promising approach for training distributed machine learning models while preserving clients’ data privacy. However, in real-world FL systems, data are often not independent and identically distributed (non-IID)…
- Energy-aware multi-agent sand-table formation control via cross-layer SAC–GNN and federated learningRuting Li, Wenni Xiao, Yan Sun, Wei Jiang · Discover Artificial Intelli... · Jul 20, 2026
In scaled-down sand table multi-agent formation experiments, existing control strategies often focus on path accuracy or formation stability, neglecting energy consumption constraints. This leads to a lack of energy awareness and inefficien…
- Federated TinyML and digital twin framework for secure and resilient IoMT-based ICU monitoringUmar Hayat Khan, Rahim Khan, Tahani Alsaedi, Samia Allaoua Chelloug et al. · Scientific Reports · Jul 19, 2026
Resource-constrained medical sensing devices are increasingly expected to support local intelligence, privacy-preserving collaboration, and secure communication in Internet of Medical Things (IoMT) environments. However, deploying federated…
- Quantum Federated Learning Framework for Privacy-Preserving Real-Time Consumer Sentiment AnalysisHong Zhen Yu, Hazirah Bee Binti Yusof Ali, M. Kazem Chamran · International Journal of Ac... · Jul 19, 2026
HRMARS - This paper introduces a new Quantum Federated Learning (QFL) system that combines quantum-enhanced transformers and federated learning to make it possible to perform real-time consumer sentiment analysis securely, at scale, and eff…
- NeuroFATE-MS: Privacy-Aware Federated Temporal Learning for Short-Term Multiple Sclerosis Progression PredictionMehmet Akif Çifçi, Peren Jerfi Canatalay · Machine Learning and Knowle... · Jul 19, 2026
Predicting short-term progression in multiple sclerosis (MS) from longitudinal clinical data remains challenging because visits occur at irregular intervals, patient trajectories vary substantially, and simulated federated clients often exh…
- Privacy-preserving messaging for medical device networksRachmad Andri Atmoko, Salnan Ratih Asriningtias, Akas Bagus Setiawan, Devasis Pradhan et al. · TELKOMNIKA (Telecommunicati... · Jul 19, 2026
Internet of medical things (IoMT) deployments rely on lightweight messaging, but the message queuing telemetry transport (MQTT) protocol still exposes sensitive metadata through plaintext topic names and stable client identifiers. In health…
- Quantum Federated Lasso With Anonymous Consensus Built Upon Quantum BlockchainLiwei Lin, Yue Wu, Chuan Huang, J M Chen et al. · Software Practice and Exper... · Jul 18, 2026
ABSTRACT Objective With the rapid advancement of quantum computing technologies, Quantum Federated Learning (QFL) has emerged as a promising framework for privacy‐preserving quantum machine learning (QML). QFL provides a promising approach …
- Federated graph learning with spatio-temporal dynamics for cross-border recommendationZhizhong Tan, Yuxing Wang, Jiexin Zheng, Ningning Zhang et al. · Scientific Reports · Jul 18, 2026
Abstract Cross-border data sharing is strictly constrained by privacy regulations, which presents a critical challenge for recommendation systems due to the severe shortage of training data. Existing federated graph neural network methods p…
- FEDERATED LEARNING YANAŞMASI ILƏ MƏXFILIK QORUNAN NLP MODELLƏRININ QURULMASIƏsgərova Aysu Məzahir Qızı Mingəçevir, Dövlət Universiteti · OpenAlex · Jul 17, 2026
- Federated causal discovery in medicine: trends, opportunities, and challengesNiccolò Rocchi, Marco Scutari, Alessio Zanga, Radha Nagarajan et al. · Frontiers in Digital Health · Jul 17, 2026
Exponential growth and continued digitisation have accelerated the adoption of data-driven and evidence-based approaches in medicine. This includes deciphering associations, including potential causal associations, from multivariate observa…
- Federated Deep Learning for Internet of Medical Things: A Comprehensive Survey of Architectures, Healthcare Applications, Privacy Preservation, Security, and Future Research DirectionsDr. Tukaram A. Chavan Dr. Vijaysinh G. Chavan · Zenodo (CERN European Organ... · Jul 17, 2026
Abstract — The rapid integration of the Internet of Things (IoT) into healthcare has enabled continuous patient monitoring, remote diagnosis, personalized treatment, and real-time clinical decision support. Internet of Medical Things (IoMT)…
- Asynchronous proximal federated aggregation for heterogeneous healthcare networksManakkattu Sreelakshmi, Radhakrishnan Delhibabu · Frontiers in Digital Health · Jul 17, 2026
Introduction The deployment of Federated Learning (FL) across the Internet of Medical Things (IoMT) is severely hindered by computational asymmetry and statistical heterogeneity. Traditional synchronous aggregation protocols suffer from sev…
- FLiPD: Privacy-Preserving Federated Learning via Multi-Party Computation and Differential PrivacyGowri R Chandran, Melek Önen, T Schneider · HAL (Le Centre pour la Comm... · Jul 16, 2026
International audience...
- Privacy-aware vaccine recommendation using federated learning and blockchainC. K. Shinzeer, Avinash Bhagat, Ajay Shriram Kushwaha · Scientific Reports · Jul 15, 2026
Suitable vaccines for individuals are suggested by the vaccine recommendation system regarding certain criteria. Nevertheless, the existing studies didn’t augment the vaccine recommendation system centered on users’ symptoms and medical his…
- Privacy-aware eye disease diagnosis using federated learning with swin transformerAbdul Sami, Mushaf Ali, Fazila Malik, Qazi Waqas Khan et al. · PeerJ Computer Science · Jul 15, 2026
Early and correct identification of eye disease is essential in preventing vision loss and blindness. However, machine learning methods require centralized data, which raises concerns about healthcare privacy and security. To address these …
- Flip-med: federated learning for innovative precision medicine - enhancing data privacy and predictive performanceRahul Haripriya, Nilay Khare, Manish Pandey, Sreemoyee Biswas · Knowledge and Information S... · Jul 15, 2026
- Modeling Secure and Efficient Quantum Federated Learning of Vehicular NetworksShanika Nanayakkara, Shiva Pokhrel · Zenodo (CERN European Organ... · Jul 14, 2026
Abstract—Vehicular quantum federated learning (QFL) enables vehicles and edge nodes to jointly train models without sharing raw mobility data. However, it faces two major challenges: high communication cost and weak protection against conte…
- Communication-Efficient Deep Unfolded Quantum Federated LearningShanika Nanayakkara, Shiva Pokhrel · Zenodo (CERN European Organ... · Jul 14, 2026
Abstract—We present Teleportation-aware Deep-Unfolded Quantum Federated Learning (tDuQFL), a topology-aware communication framework that couples deep-unfolded optimization with quantum-inspired network protocols. tDuQFL employs teleportatio…