Awesome Communication

Key papers

• Better Generative Replay for Continual Federated Learning (2023)
  Daiqing Qi et al.
  8.60
• FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models (2025)
  Hui Lin et al.
  7.44
• 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
• Enhanced Privacy and Communication Efficiency in Non-IID Federated Learning with Adaptive Quantization and Differential Privacy (2026)
  Emre Ardıç et al.
  6.52
• One-Shot Federated Learning with Classifier-Free Diffusion Models (2025)
  Obaidullah Zaland et al.
  5.24
• UAV-Assisted Multi-Task Federated Learning with Task Knowledge Sharing (2025)
  Yubo Yang et al.
  5.18
• A Tight Theory of Error Feedback Algorithms in Distributed Optimization (2026)
  Daniel Berg Thomsen et al.
  4.95
• Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection (2024)
  Liangqi Yuan et al.
  4.90
• 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
• 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
• 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
• Multi-Factor Trust-Driven Secure Communication Model for Cloud-Based Digital Twins (2026)
  Deepika Saxena et al.
  4.33
• Semantic-aware Token Selection and Resource Optimization for Communication-efficient Split Federated Fine-tuning in Edge Intelligence (2026)
  Xianke Qiang et al.
  4.33
• Provably Communication-Efficient and Privacy-Preserving Federated Graph Neural Networks (2026)
  Zhishuai Guo et al.
  4.33
• Totoro$^+$: An Adaptive and Scalable Edge Federated Learning System (2026)
  Cheng-Wei Ching et al.
  4.33
• Bandwidth Allocation with Device Partitioning for Federated Learning over Industrial IoT networks (2026)
  Kangmin Kim et al.
  4.33
• DG-CoLearn: An Efficient Collaborative Learning Framework for Dynamic Graphs (2026)
  Ashley Hoi-Ting Au et al.
  4.33
• Rate-My-LoRA: Efficient and Adaptive Federated Model Tuning for Cardiac MRI Segmentation (2025)
  Xiaoxiao He et al.
  4.25
• Over-the-Air Fair Federated Learning via Multi-Objective Optimization (2025)
  Shayan Mohajer Hamidi et al.
  4.25
• Personalized Federated Learning for Cellular VR: Online Learning and Dynamic Caching (2025)
  Krishnendu S. Tharakan et al.
  4.25
• Byzantine-Robust Federated Learning over Ring-All-Reduce Distributed Computing (2025)
  Minghong Fang et al.
  4.25
• Distributed Adaptive Learning Under Communication Constraints (2021)
  Marco Carpentiero et al.
  4.13
• FedICT: Federated Multi-task Distillation for Multi-access Edge Computing (2023)
  Zhiyuan Wu et al.
  4.13
• Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization (2024)
  Khiem Le et al.
  4.08
• From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare (2024)
  Ming Li et al.
  4.03
• Federated Hierarchical Reinforcement Learning for Adaptive Traffic Signal Control (2025)
  Yongjie Fu et al.
  3.75
• Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence (2025)
  Ratun Rahman
  3.75
• Enhancing Efficiency in Multidevice Federated Learning through Data Selection (2022)
  Fan Mo et al.
  3.71
• Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering (2022)
  Shahryar Zehtabi et al.
  3.71
• Federated Continual Learning: Concepts, Challenges, and Solutions (2025)
  Parisa Hamedi et al.
  3.64
• Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions (2025)
  Na Yan et al.
  3.59
• Towards Federated Multi-Armed Bandit Learning for Content Dissemination using Swarm of UAVs (2025)
  Amit Kumar Bhuyan et al.
  3.59
• Communication-Efficient Federated Learning Based on Explanation-Guided Pruning for Remote Sensing Image Classification (2025)
  Jonas Klotz et al.
  3.59
• Optimal Strategies for Federated Learning Maintaining Client Privacy (2025)
  Uday Bhaskar et al.
  3.59
• FedMeld: A Model-dispersal Federated Learning Framework for Space-ground Integrated Networks (2024)
  Qian Chen et al.
  3.53
• Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning (2026)
  Hengxuan Tang et al.
  3.51
• Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models (2024)
  Sajjad Ghiasvand et al.
  3.42
• Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis (2024)
  R\'emi Khellaf et al.
  3.42
• FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection (2026)
  Yutong He et al.
  3.39
• Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework (2024)
  Zilinghan Li et al.
  3.36
• FedPOD: the deployable units of training for federated learning (2025)
  Daewoon Kim et al.
  3.26
• PP-MARL: Efficient Privacy-Preserving Multi-Agent Reinforcement Learning for Cooperative Intelligence in Communications (2022)
  Tingting Yuan et al.
  3.19
• Scheduling and Aggregation Design for Asynchronous Federated Learning over Wireless Networks (2022)
  Chung-Hsuan Hu et al.
  3.19
• FedScalar: Federated Learning with Scalar Communication for Bandwidth-Constrained Networks (2024)
  M. Rostami et al.
  3.15
• pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving (2024)
  Wei-Bin Kou et al.
  3.14
• SPD-CFL: Stepwise Parameter Dropout for Efficient Continual Federated Learning (2024)
  Yuning Yang et al.
  3.14
• Anomaly Detection in Electric Vehicle Charging Stations Using Federated Learning (2025)
  Bishal K C et al.
  3.10
• SHeRL-FL: When Representation Learning Meets Split Learning in Hierarchical Federated Learning (2025)
  Dung T. Tran et al.
  3.04
• A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy (2025)
  Xiang Li et al.
  2.99
• A new type of federated clustering: A non-model-sharing approach (2025)
  Yuji Kawamata et al.
  2.93
• Split Federated Learning for Low-Altitude Wireless Networks: Joint Sensing, Communication, Computation, and Control Co-design (2025)
  Xiangwang Hou et al.
  2.82
• A Comprehensive Review on Understanding the Decentralized and Collaborative Approach in Machine Learning (2025)
  Sarwar Saif et al.
  2.76
• An Efficient Federated Learning Framework for Training Semantic Communication System (2023)
  Loc X. Nguyen et al.
  2.75
• Robust Federated Finetuning of LLMs via Alternating Optimization of LoRA (2025)
  Shuangyi Chen et al.
  2.71