{"total":16,"rows":[{"id":"2403.14101","title":"Text-Enhanced Data-free Approach for Federated Class-Incremental Learning","created":"2024-03-21","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":"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":"2401.02329","title":"Exploring Vacant Classes in Label-Skewed Federated Learning","created":"2024-01-04","cited_by_count":10,"area":null},{"id":"2505.04979","title":"Federated Deconfounding and Debiasing Learning for Out-of-Distribution Generalization","created":"2025-05-08","cited_by_count":4,"area":null},{"id":"2409.07734","title":"DFDG: Data-Free Dual-Generator Adversarial Distillation for One-Shot Federated Learning","created":"2024-09-12","cited_by_count":2,"area":null},{"id":"2502.16832","title":"FedBM: Stealing Knowledge from Pre-trained Language Models for Heterogeneous Federated Learning","created":"2025-02-24","cited_by_count":2,"area":null},{"id":"2501.15257","title":"Towards Communication-Efficient Adversarial Federated Learning for Robust Edge Intelligence","created":"2025-01-25","cited_by_count":1,"area":null},{"id":"2502.08518","title":"FedMHO: Heterogeneous One-Shot Federated Learning Towards Resource-Constrained Edge Devices","created":"2025-02-12","cited_by_count":1,"area":null},{"id":"2503.06028","title":"Data-Free Black-Box Federated Learning via Zeroth-Order Gradient Estimation","created":"2025-03-08","cited_by_count":1,"area":null},{"id":"2506.01327","title":"Enhancing Federated Class-Incremental Learning via Spatial-Temporal Statistics Aggregation","created":"2025-06-02","cited_by_count":1,"area":null},{"id":"2507.22330","title":"Hypernetworks for Model-Heterogeneous Personalized Federated Learning","created":"2025-07-30","cited_by_count":1,"area":null},{"id":"2410.06490","title":"Adaptive Guidance for Local Training in Heterogeneous Federated Learning","created":"2024-10-09","cited_by_count":0,"area":null},{"id":"2508.17381","title":"DART: A Server-side Plug-in for Resource-efficient Robust Federated Learning","created":"2025-08-24","cited_by_count":0,"area":null},{"id":"2606.10595","title":"From Data Heterogeneity to Convergence: A Data-Centric Review of Federated Learning","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2610.05378","title":"Distributed Subliminal Learning: Replacing Model Updates with Random-Carrier Outputs","created":"2026-10-04","cited_by_count":0,"area":null}],"next_cursor":null}