{"total":194,"rows":[{"id":"2307.10616","title":"Heterogeneous Federated Learning: State-of-the-art and Research Challenges","created":"2023-07-20","cited_by_count":161,"area":null},{"id":"2407.18921","title":"Mobile Edge Intelligence for Large Language Models: A Contemporary Survey","created":"2024-07-09","cited_by_count":128,"area":null},{"id":"2303.15991","title":"Efficient Parallel Split Learning over Resource-constrained Wireless Edge Networks","created":"2023-03-26","cited_by_count":95,"area":null},{"id":"2104.14362","title":"From Distributed Machine Learning to Federated Learning: A Survey","created":"2021-04-29","cited_by_count":66,"area":null},{"id":"2103.10481","title":"Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations","created":"2021-03-18","cited_by_count":51,"area":null},{"id":"2111.07494","title":"Federated Learning for Internet of Things: Applications, Challenges, and Opportunities","created":"2021-11-15","cited_by_count":50,"area":null},{"id":"2103.14272","title":"Hierarchical Federated Learning with Quantization: Convergence Analysis and System Design","created":"2021-03-26","cited_by_count":47,"area":null},{"id":"2108.09749","title":"Flexible Clustered Federated Learning for Client-Level Data Distribution Shift","created":"2021-08-22","cited_by_count":47,"area":null},{"id":"2106.09580","title":"Optimality and Stability in Federated Learning: A Game-theoretic Approach","created":"2021-06-17","cited_by_count":40,"area":null},{"id":"2206.08330","title":"Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data","created":"2022-06-16","cited_by_count":36,"area":null},{"id":"2108.09103","title":"Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks","created":"2021-08-20","cited_by_count":35,"area":null},{"id":"2204.08125","title":"FedKL: Tackling Data Heterogeneity in Federated Reinforcement Learning by Penalizing KL Divergence","created":"2022-04-18","cited_by_count":29,"area":null},{"id":"2105.00872","title":"Convergence Analysis and System Design for Federated Learning over Wireless Networks","created":"2021-04-30","cited_by_count":25,"area":null},{"id":"2302.02573","title":"Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey","created":"2023-02-06","cited_by_count":23,"area":null},{"id":"2304.13267","title":"Bayesian Federated Learning: A Survey","created":"2023-04-26","cited_by_count":22,"area":null},{"id":"2106.15734","title":"UAV-assisted Online Machine Learning over Multi-Tiered Networks: A Hierarchical Nested Personalized Federated Learning Approach","created":"2021-06-29","cited_by_count":20,"area":null},{"id":"2112.00925","title":"Context-Aware Online Client Selection for Hierarchical Federated Learning","created":"2021-12-02","cited_by_count":20,"area":null},{"id":"2407.00113","title":"Personalized Federated Continual Learning via Multi-granularity Prompt","created":"2024-06-27","cited_by_count":20,"area":null},{"id":"2105.01798","title":"Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence","created":"2021-05-04","cited_by_count":18,"area":null},{"id":"2202.02947","title":"Parallel Successive Learning for Dynamic Distributed Model Training over Heterogeneous Wireless Networks","created":"2022-02-07","cited_by_count":18,"area":null},{"id":"2205.13054","title":"Scalable and Low-Latency Federated Learning with Cooperative Mobile Edge Networking","created":"2022-05-25","cited_by_count":18,"area":null},{"id":"2101.02373","title":"Architectural Patterns for the Design of Federated Learning Systems","created":"2021-01-07","cited_by_count":17,"area":null},{"id":"2301.06447","title":"HiFlash: Communication-Efficient Hierarchical Federated Learning with Adaptive Staleness Control and Heterogeneity-aware Client-Edge Association","created":"2023-01-16","cited_by_count":17,"area":null},{"id":"2108.00365","title":"A Decentralized Federated Learning Framework via Committee Mechanism with Convergence Guarantee","created":"2021-08-01","cited_by_count":16,"area":null},{"id":"2205.10998","title":"Semi-Decentralized Federated Learning with Collaborative Relaying","created":"2022-05-23","cited_by_count":16,"area":null},{"id":"2404.08564","title":"Federated Distillation: A Survey","created":"2024-04-02","cited_by_count":15,"area":null},{"id":"2301.00519","title":"Holistic Network Virtualization and Pervasive Network Intelligence for 6G","created":"2023-01-02","cited_by_count":14,"area":null},{"id":"2310.13981","title":"Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devices","created":"2023-10-21","cited_by_count":13,"area":null},{"id":"2405.03636","title":"The Federation Strikes Back: A Survey of Federated Learning Privacy Attacks, Defenses, Applications, and Policy Landscape","created":"2024-05-06","cited_by_count":13,"area":null},{"id":"2411.12377","title":"Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions","created":"2024-11-19","cited_by_count":13,"area":null},{"id":"2104.12678","title":"Semi-Decentralized Federated Edge Learning for Fast Convergence on Non-IID Data","created":"2021-04-26","cited_by_count":12,"area":null},{"id":"2111.07392","title":"Edge-Native Intelligence for 6G Communications Driven by Federated Learning: A Survey of Trends and Challenges","created":"2021-11-14","cited_by_count":12,"area":null},{"id":"2112.10313","title":"Semi-Decentralized Federated Edge Learning with Data and Device Heterogeneity","created":"2021-12-20","cited_by_count":12,"area":null},{"id":"2210.13111","title":"Federated Learning and Meta Learning: Approaches, Applications, and Directions","created":"2022-10-24","cited_by_count":12,"area":null},{"id":"2306.12079","title":"FLGo: A Fully Customizable Federated Learning Platform","created":"2023-06-21","cited_by_count":12,"area":null},{"id":"2405.09839","title":"Advances in Robust Federated Learning: A Survey with Heterogeneity Considerations","created":"2024-05-16","cited_by_count":12,"area":null},{"id":"2112.11167","title":"Hierarchical Over-the-Air Federated Edge Learning","created":"2021-12-21","cited_by_count":11,"area":null},{"id":"2301.06646","title":"Async-HFL: Efficient and Robust Asynchronous Federated Learning in Hierarchical IoT Networks","created":"2023-01-17","cited_by_count":11,"area":null},{"id":"2401.09656","title":"Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks","created":"2024-01-18","cited_by_count":11,"area":null},{"id":"2403.02619","title":"Training Machine Learning models at the Edge: A Survey","created":"2024-03-05","cited_by_count":11,"area":null},{"id":"2101.03627","title":"Bandwidth Allocation for Multiple Federated Learning Services in Wireless Edge Networks","created":"2021-01-10","cited_by_count":10,"area":null},{"id":"2104.13215","title":"A Graph Federated Architecture with Privacy Preserving Learning","created":"2021-04-26","cited_by_count":10,"area":null},{"id":"2105.04153","title":"Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates","created":"2021-05-10","cited_by_count":10,"area":null},{"id":"2107.06548","title":"Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems with Imbalanced Data","created":"2021-07-14","cited_by_count":10,"area":null},{"id":"2203.06900","title":"Communication-Efficient Federated Distillation with Active Data Sampling","created":"2022-03-14","cited_by_count":10,"area":null},{"id":"2203.13950","title":"Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point","created":"2022-03-26","cited_by_count":10,"area":null},{"id":"2207.09232","title":"Over-the-Air Federated Edge Learning with Hierarchical Clustering","created":"2022-07-19","cited_by_count":10,"area":null},{"id":"2301.03062","title":"AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices","created":"2023-01-08","cited_by_count":10,"area":null},{"id":"2305.09042","title":"Adaptive Federated Pruning in Hierarchical Wireless Networks","created":"2023-05-15","cited_by_count":10,"area":null},{"id":"2308.01562","title":"Hierarchical Federated Learning in Wireless Networks: Pruning Tackles Bandwidth Scarcity and System Heterogeneity","created":"2023-08-03","cited_by_count":10,"area":null},{"id":"2310.10089","title":"Over-the-Air Federated Learning and Optimization","created":"2023-10-16","cited_by_count":10,"area":null},{"id":"2312.11489","title":"Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration","created":"2023-12-01","cited_by_count":10,"area":null},{"id":"2106.11570","title":"FLRA: A Reference Architecture for Federated Learning Systems","created":"2021-06-22","cited_by_count":9,"area":null},{"id":"2109.03999","title":"Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies","created":"2021-09-09","cited_by_count":9,"area":null},{"id":"2303.12414","title":"Delay-Aware Hierarchical Federated Learning","created":"2023-03-22","cited_by_count":9,"area":null},{"id":"2302.04851","title":"Delay Sensitive Hierarchical Federated Learning with Stochastic Local Updates","created":"2023-02-09","cited_by_count":8,"area":null},{"id":"2409.19560","title":"Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving","created":"2024-09-29","cited_by_count":8,"area":null},{"id":"2505.00365","title":"SacFL: Self-Adaptive Federated Continual Learning for Resource-Constrained End Devices","created":"2025-05-01","cited_by_count":8,"area":null},{"id":"2102.03620","title":"Multi-Tier Federated Learning for Vertically Partitioned Data","created":"2021-02-06","cited_by_count":7,"area":null},{"id":"2204.00215","title":"Federated Learning Framework Coping with Hierarchical Heterogeneity in Cooperative ITS","created":"2022-04-01","cited_by_count":7,"area":null},{"id":"2302.11466","title":"Advancements in Federated Learning: Models, Methods, and Privacy","created":"2023-02-22","cited_by_count":7,"area":null},{"id":"2305.05118","title":"Flame: Simplifying Topology Extension in Federated Learning","created":"2023-05-09","cited_by_count":7,"area":null},{"id":"2409.18448","title":"Hierarchical Federated Learning with Multi-Timescale Gradient Correction","created":"2024-09-27","cited_by_count":7,"area":null},{"id":"2107.02755","title":"FedFog: Network-Aware Optimization of Federated Learning over Wireless Fog-Cloud Systems","created":"2021-07-04","cited_by_count":6,"area":null},{"id":"2108.08930","title":"Cross-Silo Federated Learning for Multi-Tier Networks with Vertical and Horizontal Data Partitioning","created":"2021-08-19","cited_by_count":6,"area":null},{"id":"2112.01039","title":"How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning","created":"2021-12-02","cited_by_count":6,"area":null},{"id":"2210.14560","title":"Hierarchical Federated Learning with Momentum Acceleration in Multi-Tier Networks","created":"2022-10-26","cited_by_count":6,"area":null},{"id":"2402.02506","title":"Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Things","created":"2024-02-04","cited_by_count":6,"area":null},{"id":"2505.04873","title":"Federated Learning for Cyber Physical Systems: A Comprehensive Survey","created":"2025-05-08","cited_by_count":6,"area":null},{"id":"2107.05330","title":"Sparse Personalized Federated Learning","created":"2021-07-12","cited_by_count":5,"area":null},{"id":"2202.11850","title":"Robust Federated Learning with Connectivity Failures: A Semi-Decentralized Framework with Collaborative Relaying","created":"2022-02-24","cited_by_count":5,"area":null},{"id":"2204.04254","title":"HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection","created":"2022-04-08","cited_by_count":5,"area":null},{"id":"2205.09529","title":"Mobility, Communication and Computation Aware Federated Learning for Internet of Vehicles","created":"2022-05-17","cited_by_count":5,"area":null},{"id":"2209.14900","title":"Joint Optimization of Energy Consumption and Completion Time in Federated Learning","created":"2022-09-29","cited_by_count":5,"area":null},{"id":"2212.01215","title":"Olive Branch Learning: A Topology-Aware Federated Learning Framework for Space-Air-Ground Integrated Network","created":"2022-12-02","cited_by_count":5,"area":null},{"id":"2311.07324","title":"Data-Aware Gradient Compression for FL in Communication-Constrained Mobile Computing","created":"2023-11-13","cited_by_count":5,"area":null},{"id":"2312.15361","title":"Cooperative Federated Learning over Ground-to-Satellite Integrated Networks: Joint Local Computation and Data Offloading","created":"2023-12-23","cited_by_count":5,"area":null},{"id":"2401.09986","title":"Improving Local Training in Federated Learning via Temperature Scaling","created":"2024-01-18","cited_by_count":5,"area":null},{"id":"2405.14446","title":"Worldwide Federated Training of Language Models","created":"2024-05-23","cited_by_count":5,"area":null},{"id":"2407.12410","title":"Proximity-based Self-Federated Learning","created":"2024-07-17","cited_by_count":5,"area":null},{"id":"2502.08577","title":"FBFL: A Field-Based Coordination Approach for Data Heterogeneity in Federated Learning","created":"2025-02-12","cited_by_count":5,"area":null},{"id":"2503.20618","title":"ProFed: a Benchmark for Proximity-based non-IID Federated Learning","created":"2025-03-26","cited_by_count":5,"area":null},{"id":"2602.02458","title":"Conflict-Aware Client Selection for Multi-Server Federated Learning","created":"2026-02-02","cited_by_count":5,"area":null},{"id":"2112.04737","title":"Asynchronous Semi-Decentralized Federated Edge Learning for Heterogeneous Clients","created":"2021-12-09","cited_by_count":4,"area":null},{"id":"2112.05559","title":"Collaborative Learning over Wireless Networks: An Introductory Overview","created":"2021-12-07","cited_by_count":4,"area":null},{"id":"2203.13517","title":"Sparse Federated Learning with Hierarchical Personalized Models","created":"2022-03-25","cited_by_count":4,"area":null},{"id":"2204.00489","title":"Accelerating Federated Edge Learning via Topology Optimization","created":"2022-04-01","cited_by_count":4,"area":null},{"id":"2204.03326","title":"Enabling All In-Edge Deep Learning: A Literature Review","created":"2022-04-07","cited_by_count":4,"area":null},{"id":"2206.00054","title":"Asynchronous Hierarchical Federated Learning","created":"2022-05-31","cited_by_count":4,"area":null},{"id":"2210.04689","title":"Time Minimization in Hierarchical Federated Learning","created":"2022-10-07","cited_by_count":4,"area":null},{"id":"2212.10427","title":"ModularFed: Leveraging Modularity in Federated Learning Frameworks","created":"2022-10-31","cited_by_count":4,"area":null},{"id":"2303.07452","title":"Network Anomaly Detection Using Federated Learning","created":"2023-03-13","cited_by_count":4,"area":null},{"id":"2306.00675","title":"RHFedMTL: Resource-Aware Hierarchical Federated Multi-Task Learning","created":"2023-06-01","cited_by_count":4,"area":null},{"id":"2306.06399","title":"Personalized Graph Federated Learning with Differential Privacy","created":"2023-06-10","cited_by_count":4,"area":null},{"id":"2312.04688","title":"Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights","created":"2023-12-07","cited_by_count":4,"area":null},{"id":"2402.04216","title":"Resource-Aware Hierarchical Federated Learning in Wireless Video Caching Networks","created":"2024-02-06","cited_by_count":4,"area":null},{"id":"2405.20431","title":"Exploring the Practicality of Federated Learning: A Survey Towards the Communication Perspective","created":"2024-05-30","cited_by_count":4,"area":null},{"id":"2407.09873","title":"Resource Management for Low-latency Cooperative Fine-tuning of Foundation Models at the Network Edge","created":"2024-07-13","cited_by_count":4,"area":null},{"id":"2503.21213","title":"Resource-Efficient Federated Fine-Tuning Large Language Models for Heterogeneous Data","created":"2025-03-27","cited_by_count":4,"area":null},{"id":"2109.14334","title":"Secure Multi-Party Computation based Privacy Preserving Data Analysis in Healthcare IoT Systems","created":"2021-09-29","cited_by_count":3,"area":null}],"next_cursor":"100"}