Awesome Federated Learning

Key papers

• Federated Adversarial Domain Adaptation (2019)
  Xingchao Peng et al.
  10.99
• A Survey on Decentralized Federated Learning (2023)
  Edoardo Gabrielli et al.
  10.32
• Better Generative Replay for Continual Federated Learning (2023)
  Daiqing Qi et al.
  8.60
• FederBoost: Private Federated Learning for GBDT (2020)
  Zhihua Tian et al.
  8.19
• Federated Domain Generalization: A Survey (2023)
  Ying Li et al.
  7.59
• Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data (2021)
  Zilong Zhao et al.
  7.50
• When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions (2023)
  Weiming Zhuang et al.
  7.50
• FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models (2025)
  Hui Lin et al.
  7.44
• Deep Anatomical Federated Network (Dafne): An open client-server framework for the continuous, collaborative improvement of deep learning-based medical image segmentation (2023)
  Francesco Santini et al.
  7.01
• Knowledge Distillation for Federated Learning: a Practical Guide (2022)
  Alessio Mora et al.
  6.78
• On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach (2026)
  Jiahui Bai et al.
  6.72
• Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning (2020)
  Xinjian Luo et al.
  6.66
• Do We Really Need to Design New Byzantine-robust Aggregation Rules? (2025)
  Minghong Fang et al.
  6.58
• Personalized Semi-Supervised Federated Learning for Human Activity Recognition (2021)
  Riccardo Presotto et al.
  6.53
• Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy (2026)
  Emre Ardıç et al.
  6.52
• Fair and efficient contribution valuation for vertical federated learning (2022)
  Zhenan Fan et al.
  6.39
• Advances and Challenges in Meta-Learning: A Technical Review (2023)
  Anna Vettoruzzo et al.
  6.39
• Differentially Private Federated Learning: A Systematic Review (2024)
  Jie Fu et al.
  6.33
• Advancing MRI Reconstruction: A Systematic Review of Deep Learning and Compressed Sensing Integration (2025)
  Mojtaba Safari et al.
  6.12
• Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case (2025)
  William Marfo et al.
  6.12
• PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark (2023)
  Jianqing Zhang et al.
  5.86
• LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data (2025)
  Yuxin Zhang et al.
  5.84
• AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks (2024)
  Zheng Lin et al.
  5.80
• Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training? (2021)
  Shuxiao Chen et al.
  5.72
• Energy-Latency Attacks via Sponge Poisoning (2022)
  Antonio Emanuele Cin\`a et al.
  5.72
• Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems (2025)
  William Marfo et al.
  5.54
• Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis (2024)
  Guangchen Lan et al.
  5.34
• Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications (2023)
  Francesco Cremonesi et al.
  5.30
• One-Shot Federated Learning with Classifier-Free Diffusion Models (2025)
  Obaidullah Zaland et al.
  5.24
• AFed: Algorithmic Fair Federated Learning (2025)
  Huiqiang Chen et al.
  5.18
• FedSA: A Unified Representation Learning via Semantic Anchors for Prototype-based Federated Learning (2025)
  Yanbing Zhou et al.
  5.18
• UAV-Assisted Multi-Task Federated Learning with Task Knowledge Sharing (2025)
  Yubo Yang et al.
  5.18
• Federated Learning with Sample-level Client Drift Mitigation (2025)
  Haoran Xu et al.
  5.18
• Unlearning Clients, Features and Samples in Vertical Federated Learning (2025)
  Ayush K. Varshney et al.
  5.18
• FedDTG:Federated Data-Free Knowledge Distillation via Three-Player Generative Adversarial Networks (2022)
  Lingzhi Gao et al.
  5.06
• Federated Transfer Learning with Differential Privacy (2024)
  Mengchu Li et al.
  5.02
• Post-Quantum Secure Federated DeFi for Inclusive Banking (2026)
  Swati Sachan et al.
  5.01
• Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems (2024)
  Ayoub Si-ahmed et al.
  4.98
• Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction (2025)
  Yazan Otoum et al.
  4.93
• Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection (2024)
  Liangqi Yuan et al.
  4.90
• PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning (2025)
  Yu Feng et al.
  4.82
• Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks (2025)
  Shuai Wang et al.
  4.76
• Distributed Intrusion Detection in Dynamic Networks of UAVs using Few-Shot Federated Learning (2025)
  Ozlem Ceviz et al.
  4.76
• A Two-Stage CAE-Based Federated Learning Framework for Efficient Jamming Detection in 5G Networks (2025)
  Samhita Kuili et al.
  4.76
• Decentralized Low-Rank Fine-Tuning of Large Language Models (2025)
  Sajjad Ghiasvand et al.
  4.76
• Interplay between Federated Learning and Explainable Artificial Intelligence: a Scoping Review (2024)
  Luis M. Lopez-Ramos et al.
  4.65
• Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities (2024)
  Zikai Zhang et al.
  4.54
• Federated Large Language Models: Current Progress and Future Directions (2024)
  Yuhang Yao et al.
  4.54
• Elastic Federated Learning over Open Radio Access Network (O-RAN) for Concurrent Execution of Multiple Distributed Learning Tasks (2023)
  Payam Abdisarabshali et al.
  4.52
• Federated Multi-Armed Bandits Under Byzantine Attacks (2022)
  Artun Saday et al.
  4.48
• Federated Learning in Adversarial Environments: Testbed Design and Poisoning Resilience in Cybersecurity (2024)
  Hao Jian Huang et al.
  4.41
• QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning (2026)
  Nazmus Shakib Shadin et al.
  4.39
• FedSteer: Taming Extreme Gradient Staleness in Federated Learning with Corrective Projections and Caching (2026)
  Haoran Zhang et al.
  4.39
• Compositional Generative Modeling from Decentralized Data (2026)
  Mashrur M. Morshed et al.
  4.39
• Multi-Level Analyzation of Imbalance to Resolve Non-IID-Ness in Federated Learning (2026)
  Haengbok Chung et al.
  4.39
• MoE Enhanced Federated Learning for Spatiotemporal Prediction (2026)
  Zhehao Dai et al.
  4.39
• Inverse Probability Weighting and Age-of-Information Aggregation for Decentralized Federated Learning under Partial Reception (2026)
  Chanuka A. S. Hewa Kaluannakkage et al.
  4.39
• Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT (2025)
  Xiaohong Yang et al.
  4.36
• Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers and Gradient Clipping (2023)
  Martin Pelikan et al.
  4.35
• FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning (2026)
  Rachid Hedjam
  4.33