{"total":18,"rows":[{"id":"2209.10083","title":"Federated Learning from Pre-Trained Models: A Contrastive Learning Approach","created":"2022-09-21","cited_by_count":142,"area":null},{"id":"2211.13009","title":"Federated Learning on Non-IID Graphs via Structural Knowledge Sharing","created":"2022-11-23","cited_by_count":88,"area":null},{"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":"2302.09479","title":"Delving into the Adversarial Robustness of Federated Learning","created":"2023-02-19","cited_by_count":19,"area":null},{"id":"2302.06079","title":"Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting","created":"2023-02-13","cited_by_count":14,"area":null},{"id":"2306.05879","title":"FedWon: Triumphing Multi-domain Federated Learning Without Normalization","created":"2023-06-09","cited_by_count":11,"area":null},{"id":"2410.15042","title":"Adversarial Training: A Survey","created":"2024-10-19","cited_by_count":6,"area":null},{"id":"2212.01976","title":"FedCC: Robust Federated Learning against Model Poisoning Attacks","created":"2022-12-05","cited_by_count":5,"area":null},{"id":"2403.02803","title":"Towards Robust Federated Learning via Logits Calibration on Non-IID Data","created":"2024-03-05","cited_by_count":5,"area":null},{"id":"2404.06776","title":"Logit Calibration and Feature Contrast for Robust Federated Learning on Non-IID Data","created":"2024-04-10","cited_by_count":4,"area":null},{"id":"2210.12575","title":"Outsourcing Training without Uploading Data via Efficient Collaborative Open-Source Sampling","created":"2022-10-23","cited_by_count":3,"area":null},{"id":"2408.07966","title":"Addressing Skewed Heterogeneity via Federated Prototype Rectification with Personalization","created":"2024-08-15","cited_by_count":2,"area":null},{"id":"2410.03499","title":"FedStein: Enhancing Multi-Domain Federated Learning Through James-Stein Estimator","created":"2024-10-04","cited_by_count":1,"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":"2206.02131","title":"Federated Adversarial Training with Transformers","created":"2022-06-05","cited_by_count":0,"area":null},{"id":"2506.05402","title":"Lorica: A Synergistic Fine-Tuning Framework for Advancing Personalized Adversarial Robustness","created":"2025-06-04","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":"2512.04264","title":"Studying Various Activation Functions and Non-IID Data for Machine Learning Model Robustness","created":"2025-12-03","cited_by_count":0,"area":null}],"next_cursor":null}