{"total":20,"rows":[{"id":"2306.01603","title":"Decentralized Federated Learning: A Survey and Perspective","created":"2023-06-02","cited_by_count":86,"area":null},{"id":"2308.10407","title":"Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challenges","created":"2023-08-21","cited_by_count":40,"area":null},{"id":"2501.01293","title":"LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks","created":"2025-01-02","cited_by_count":22,"area":null},{"id":"2307.10805","title":"Communication-Efficient Split Learning via Adaptive Feature-Wise Compression","created":"2023-07-20","cited_by_count":18,"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":"2308.11953","title":"When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation","created":"2023-08-23","cited_by_count":4,"area":null},{"id":"2302.12662","title":"FedDBL: Communication and Data Efficient Federated Deep-Broad Learning for Histopathological Tissue Classification","created":"2023-02-24","cited_by_count":3,"area":null},{"id":"2408.13787","title":"Mask-Encoded Sparsification: Mitigating Biased Gradients in Communication-Efficient Split Learning","created":"2024-08-25","cited_by_count":2,"area":null},{"id":"2507.07130","title":"Ampere: Communication-Efficient and High-Accuracy Split Federated Learning","created":"2025-07-08","cited_by_count":2,"area":null},{"id":"2603.16120","title":"Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users","created":"2026-03-17","cited_by_count":2,"area":null},{"id":"2310.17890","title":"Federated Learning over Hierarchical Wireless Networks: Training Latency Minimization via Submodel Partitioning","created":"2023-10-27","cited_by_count":1,"area":null},{"id":"2402.14139","title":"NeuroFlux: Memory-Efficient CNN Training Using Adaptive Local Learning","created":"2024-02-21","cited_by_count":1,"area":null},{"id":"2603.04437","title":"ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning","created":"2026-02-19","cited_by_count":1,"area":null},{"id":"2307.15870","title":"SemiSFL: Split Federated Learning on Unlabeled and Non-IID Data","created":"2023-07-29","cited_by_count":0,"area":null},{"id":"2311.02399","title":"Entropy Aware Training for Fast and Accurate Distributed GNN","created":"2023-11-04","cited_by_count":0,"area":null},{"id":"2403.18439","title":"Generalized Policy Learning for Smart Grids: FL TRPO Approach","created":"2024-03-27","cited_by_count":0,"area":null},{"id":"2411.06042","title":"Personalized Hierarchical Split Federated Learning in Wireless Networks","created":"2024-11-09","cited_by_count":0,"area":null},{"id":"2412.20946","title":"Generalising Battery Control in Net-Zero Buildings via Personalised Federated RL","created":"2024-12-30","cited_by_count":0,"area":null},{"id":"2504.13850","title":"FedOptima: Optimizing Resource Utilization in Federated Learning","created":"2025-03-10","cited_by_count":0,"area":null},{"id":"2505.14081","title":"Personalized and Resilient Distributed Learning Through Opinion Dynamics","created":"2025-05-20","cited_by_count":0,"area":null}],"next_cursor":null}