{"total":36,"rows":[{"id":"2404.15381","title":"Advances and Open Challenges in Federated Foundation Models","created":"2024-04-23","cited_by_count":36,"area":null},{"id":"2409.15723","title":"Federated Large Language Models: Current Progress and Future Directions","created":"2024-09-24","cited_by_count":27,"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":"2402.05968","title":"Federated Learning Priorities Under the European Union Artificial Intelligence Act","created":"2024-02-05","cited_by_count":13,"area":null},{"id":"2405.03636","title":"The Federation Strikes Back: A Survey of Federated Learning Privacy Attacks, Defenses, Applications, and Policy Landscape","created":"2024-05-06","cited_by_count":13,"area":null},{"id":"2308.03573","title":"When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection","created":"2023-08-07","cited_by_count":7,"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":"2310.10665","title":"Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey","created":"2023-09-19","cited_by_count":3,"area":null},{"id":"2410.06340","title":"FedGraph: A Research Library and Benchmark for Federated Graph Learning","created":"2024-10-08","cited_by_count":3,"area":null},{"id":"2506.21735","title":"Equitable Federated Learning with NCA","created":"2025-06-26","cited_by_count":3,"area":null},{"id":"2405.10376","title":"Dealing Doubt: Unveiling Threat Models in Gradient Inversion Attacks under Federated Learning, A Survey and Taxonomy","created":"2024-05-16","cited_by_count":2,"area":null},{"id":"2411.05260","title":"QuanCrypt-FL: Quantized Homomorphic Encryption with Pruning for Secure Federated Learning","created":"2024-11-08","cited_by_count":2,"area":null},{"id":"2508.11848","title":"Adversarial Robustness in Distributed Quantum Machine Learning","created":"2025-08-16","cited_by_count":2,"area":null},{"id":"2508.13730","title":"On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions","created":"2025-08-19","cited_by_count":2,"area":null},{"id":"2511.06064","title":"A Privacy-Preserving Federated Learning Method with Homomorphic Encryption in Omics Data","created":"2025-11-08","cited_by_count":2,"area":null},{"id":"2512.01025","title":"Operator-Theoretic Framework for Gradient-Free Federated Learning","created":"2025-11-30","cited_by_count":2,"area":null},{"id":"2410.18114","title":"Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond","created":"2024-10-09","cited_by_count":1,"area":null},{"id":"2503.03684","title":"Towards Trustworthy Federated Learning","created":"2025-03-05","cited_by_count":1,"area":null},{"id":"2508.18911","title":"Enhancing Model Privacy in Federated Learning with Random Masking and Quantization","created":"2025-08-26","cited_by_count":1,"area":null},{"id":"2510.21086","title":"DictPFL: Efficient and Private Federated Learning on Encrypted Gradients","created":"2025-10-24","cited_by_count":1,"area":null},{"id":"2602.22269","title":"CQSA: Byzantine-robust Clustered Quantum Secure Aggregation in Federated Learning","created":"2026-02-25","cited_by_count":1,"area":null},{"id":"2603.02969","title":"Integrating Homomorphic Encryption and Synthetic Data in FL for Privacy and Learning Quality","created":"2026-03-03","cited_by_count":1,"area":null},{"id":"2308.14658","title":"Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices","created":"2023-08-28","cited_by_count":0,"area":null},{"id":"2405.17697","title":"P4: Towards private, personalized, and Peer-to-Peer learning","created":"2024-05-27","cited_by_count":0,"area":null},{"id":"2412.12640","title":"GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2501.02981","title":"CONTINUUM: Detecting APT Attacks through Spatial-Temporal Graph Neural Networks","created":"2025-01-06","cited_by_count":0,"area":null},{"id":"2501.12911","title":"A Selective Homomorphic Encryption Approach for Faster Privacy-Preserving Federated Learning","created":"2025-01-22","cited_by_count":0,"area":null},{"id":"2504.02213","title":"Secure Generalization through Stochastic Bidirectional Parameter Updates Using Dual-Gradient Mechanism","created":"2025-04-03","cited_by_count":0,"area":null},{"id":"2506.20413","title":"Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning","created":"2025-06-25","cited_by_count":0,"area":null},{"id":"2507.15104","title":"AnalogFed: Privacy-Preserving Discovery of Analog Circuits at Scale with Federated Generative AI","created":"2025-07-20","cited_by_count":0,"area":null},{"id":"2508.04155","title":"Evaluating Selective Encryption Against Gradient Inversion Attacks","created":"2025-08-06","cited_by_count":0,"area":null},{"id":"2601.01649","title":"Communication-Efficient Federated AUC Maximization with Cyclic Client Participation","created":"2026-01-04","cited_by_count":0,"area":null},{"id":"2601.04912","title":"Decentralized Privacy-Preserving Federal Learning of Computer Vision Models on Edge Devices","created":"2026-01-08","cited_by_count":0,"area":null},{"id":"2602.01185","title":"FedBGS: A Blockchain Approach to Segment Gossip Learning in Decentralized Systems","created":"2026-02-01","cited_by_count":0,"area":null},{"id":"2603.05158","title":"Balancing Privacy-Quality-Efficiency in Federated Learning through Round-Based Interleaving of Protection Techniques","created":"2026-03-05","cited_by_count":0,"area":null},{"id":"2607.06612","title":"PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning","created":"2026-07-07","cited_by_count":0,"area":null}],"next_cursor":null}