{"total":26,"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":"2410.08892","title":"Federated Learning in Practice: Reflections and Projections","created":"2024-10-11","cited_by_count":15,"area":null},{"id":"2406.12844","title":"Synergizing Foundation Models and Federated Learning: A Survey","created":"2024-06-18","cited_by_count":14,"area":null},{"id":"2406.16746","title":"The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources","created":"2024-06-24","cited_by_count":11,"area":null},{"id":"2502.14584","title":"Vision Foundation Models in Medical Image Analysis: Advances and Challenges","created":"2025-02-20","cited_by_count":9,"area":null},{"id":"2505.13502","title":"Federated Low-Rank Adaptation for Foundation Models: A Survey","created":"2025-05-16","cited_by_count":9,"area":null},{"id":"2407.16560","title":"COALA: A Practical and Vision-Centric Federated Learning Platform","created":"2024-07-23","cited_by_count":7,"area":null},{"id":"2502.09104","title":"One-shot Federated Learning Methods: A Practical Guide","created":"2025-02-13","cited_by_count":6,"area":null},{"id":"2505.06907","title":"A Survey on Foundation Models for Personalized Federated Intelligence","created":"2025-05-11","cited_by_count":3,"area":null},{"id":"2509.00799","title":"Fairness in Federated Learning: Trends, Challenges, and Opportunities","created":"2025-08-31","cited_by_count":3,"area":null},{"id":"2510.12595","title":"Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practice","created":"2025-10-14","cited_by_count":3,"area":null},{"id":"2407.08105","title":"Federated Learning and AI Regulation in the European Union: Who is Responsible? -- An Interdisciplinary Analysis","created":"2024-07-11","cited_by_count":1,"area":null},{"id":"2509.05142","title":"Foundational Models and Federated Learning: Survey, Taxonomy, Challenges and Practical Insights","created":"2025-09-05","cited_by_count":1,"area":null},{"id":"2602.08617","title":"ERIS: Enhancing the Privacy-Utility-Scalability Trade-Off in Federated Learning via Federated Shard Aggregation","created":"2026-02-09","cited_by_count":1,"area":null},{"id":"2605.08992","title":"When More Parameters Hurt: Foundation Model Priors Amplify Worst-Client Disparity Under Extreme Federated Heterogeneity","created":"2026-05-09","cited_by_count":1,"area":null},{"id":"2402.16157","title":"Consensus learning: A novel decentralised ensemble learning paradigm","created":"2024-02-25","cited_by_count":0,"area":null},{"id":"2406.00004","title":"Navigating the Future of Federated Recommendation Systems with Foundation Models","created":"2024-05-12","cited_by_count":0,"area":null},{"id":"2505.23593","title":"Federated Foundation Language Model Post-Training Should Focus on Open-Source Models","created":"2025-05-29","cited_by_count":0,"area":null},{"id":"2506.02887","title":"Overcoming Challenges of Partial Client Participation in Federated Learning : A Comprehensive Review","created":"2025-06-03","cited_by_count":0,"area":null},{"id":"2507.19534","title":"FedDPG: An Adaptive Yet Efficient Prompt-tuning Approach in Federated Learning Settings","created":"2025-07-22","cited_by_count":0,"area":null},{"id":"2508.10299","title":"Improving Learning of New Diseases through Knowledge-Enhanced Initialization for Federated Adapter Tuning","created":"2025-08-14","cited_by_count":0,"area":null},{"id":"2508.16261","title":"On the Evolution of Federated Post-Training Large Language Models: A Model Accessibility View","created":"2025-08-22","cited_by_count":0,"area":null},{"id":"2602.00647","title":"CoRe-Fed: Bridging Collaborative and Representation Fairness via Federated Embedding Distillation","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2602.00718","title":"Federated Learning at the Forefront of Fairness: A Multifaceted Perspective","created":"2026-01-31","cited_by_count":0,"area":null},{"id":"2606.16891","title":"Beyond Weights and Gradients: A Taxonomy of Federated Learning Messages","created":"2026-06-15","cited_by_count":0,"area":null}],"next_cursor":null}