{"total":18,"rows":[{"id":"2310.15080","title":"Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization","created":"2023-10-23","cited_by_count":65,"area":null},{"id":"2211.13430","title":"Multi-Job Intelligent Scheduling with Cross-Device Federated Learning","created":"2022-11-24","cited_by_count":20,"area":null},{"id":"2303.08678","title":"Visual Prompt Based Personalized Federated Learning","created":"2023-03-15","cited_by_count":16,"area":null},{"id":"2312.10935","title":"AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices","created":"2023-12-18","cited_by_count":15,"area":null},{"id":"2411.01583","title":"Trustworthy Federated Learning: Privacy, Security, and Beyond","created":"2024-11-03","cited_by_count":11,"area":null},{"id":"2312.15186","title":"Efficient Asynchronous Federated Learning with Sparsification and Quantization","created":"2023-12-23","cited_by_count":9,"area":null},{"id":"2403.19178","title":"Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning","created":"2024-03-28","cited_by_count":9,"area":null},{"id":"2310.15084","title":"Quantum Federated Learning With Quantum Networks","created":"2023-10-23","cited_by_count":8,"area":null},{"id":"2403.01387","title":"A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications","created":"2024-03-03","cited_by_count":8,"area":null},{"id":"2408.05678","title":"Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data","created":"2024-08-11","cited_by_count":6,"area":null},{"id":"2410.00131","title":"Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models","created":"2024-09-30","cited_by_count":6,"area":null},{"id":"2312.08975","title":"On Mask-based Image Set Desensitization with Recognition Support","created":"2023-12-14","cited_by_count":2,"area":null},{"id":"2507.06031","title":"Efficient Federated Learning with Timely Update Dissemination","created":"2025-07-08","cited_by_count":2,"area":null},{"id":"2503.11828","title":"Performance Analysis of Decentralized Federated Learning Deployments","created":"2025-03-14","cited_by_count":1,"area":null},{"id":"2312.10425","title":"Knowledge Rumination for Client Utility Evaluation in Heterogeneous Federated Learning","created":"2023-12-16","cited_by_count":0,"area":null},{"id":"2503.05755","title":"SEAFL: Enhancing Efficiency in Semi-Asynchronous Federated Learning through Adaptive Aggregation and Selective Training","created":"2025-02-22","cited_by_count":0,"area":null},{"id":"2507.20571","title":"DAG-AFL:Directed Acyclic Graph-based Asynchronous Federated Learning","created":"2025-07-28","cited_by_count":0,"area":null},{"id":"2508.05135","title":"HFedATM: Hierarchical Federated Domain Generalization via Optimal Transport and Regularized Mean Aggregation","created":"2025-08-07","cited_by_count":0,"area":null}],"next_cursor":null}