{"total":14,"rows":[{"id":"2402.01350","title":"pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning","created":"2024-02-02","cited_by_count":24,"area":"moe"},{"id":"2411.02115","title":"FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation","created":"2024-11-04","cited_by_count":11,"area":"moe"},{"id":"2601.00583","title":"HFedMoE: Resource-aware Heterogeneous Federated Learning with Mixture-of-Experts","created":"2026-01-02","cited_by_count":11,"area":"moe"},{"id":"2502.00354","title":"PM-MOE: Mixture of Experts on Private Model Parameters for Personalized Federated Learning","created":"2025-02-01","cited_by_count":9,"area":"moe"},{"id":"2603.21276","title":"Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity","created":"2026-03-22","cited_by_count":4,"area":"moe"},{"id":"2411.07834","title":"Towards Vision Mixture of Experts for Wildlife Monitoring on the Edge","created":"2024-11-12","cited_by_count":2,"area":"moe"},{"id":"2512.23070","title":"FLEX-MoE: Federated Mixture-of-Experts with Load-balanced Expert Assignment for Edge Computing","created":"2025-12-28","cited_by_count":2,"area":"moe"},{"id":"2508.19078","title":"Federated Fine-Tuning of Sparsely-Activated Large Language Models on Resource-Constrained Devices","created":"2025-08-26","cited_by_count":1,"area":"moe"},{"id":"2511.01743","title":"Towards Efficient Federated Learning of Networked Mixture-of-Experts for Mobile Edge Computing","created":"2025-11-03","cited_by_count":1,"area":"moe"},{"id":"2506.18789","title":"Shift Happens: Mixture of Experts based Continual Adaptation in Federated Learning","created":"2025-06-23","cited_by_count":0,"area":"moe"},{"id":"2602.14301","title":"DeepFusion: Accelerating MoE Training via Federated Knowledge Distillation from Heterogeneous Edge Devices","created":"2026-02-15","cited_by_count":0,"area":"moe"},{"id":"2606.15625","title":"Conflict-Aware Federated Fine-Tuning of Large Language Models with Mixture-of-Experts","created":"2026-06-14","cited_by_count":0,"area":"moe"},{"id":"2606.19025","title":"FoMoE: Breaking the Full-Replica Barrier with a Federation of MoEs","created":"2026-06-17","cited_by_count":0,"area":"moe"},{"id":"2608.15311","title":"MoE Router-Guided Clustering for Heterogeneous Federated Instruction Tuning","created":"2026-08-15","cited_by_count":0,"area":"moe"}],"next_cursor":null}