{"total":12,"rows":[{"id":"2306.15546","title":"When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions","created":"2023-06-27","cited_by_count":84,"area":null},{"id":"2302.00903","title":"No One Left Behind: Real-World Federated Class-Incremental Learning","created":"2023-02-02","cited_by_count":53,"area":null},{"id":"2307.10655","title":"A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency","created":"2023-07-20","cited_by_count":21,"area":null},{"id":"2307.12463","title":"Rethinking Data Distillation: Do Not Overlook Calibration","created":"2023-07-24","cited_by_count":13,"area":null},{"id":"2502.12976","title":"Does Training with Synthetic Data Truly Protect Privacy?","created":"2025-02-18","cited_by_count":12,"area":null},{"id":"2406.18540","title":"Fully Exploiting Every Real Sample: SuperPixel Sample Gradient Model Stealing","created":"2024-05-18","cited_by_count":5,"area":null},{"id":"2409.14122","title":"Efficient and Effective Model Extraction","created":"2024-09-21","cited_by_count":4,"area":null},{"id":"2504.17421","title":"Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks","created":"2025-04-24","cited_by_count":4,"area":null},{"id":"2305.14403","title":"Layer-adaptive Structured Pruning Guided by Latency","created":"2023-05-23","cited_by_count":1,"area":null},{"id":"2405.16361","title":"LDPKiT: Superimposing Remote Queries for Privacy-Preserving Distillation","created":"2024-05-25","cited_by_count":1,"area":null},{"id":"2409.10643","title":"CaBaGe: Data-Free Model Extraction using ClAss BAlanced Generator Ensemble","created":"2024-09-16","cited_by_count":0,"area":null},{"id":"2509.11159","title":"Stabilizing Data-Free Model Extraction","created":"2025-09-14","cited_by_count":0,"area":null}],"next_cursor":null}