Summary of Privacy in Fine-tuning Large Language Models: Attacks, Defenses, and Future Directions, by Hao Du et al.
Privacy in Fine-tuning Large Language Models: Attacks, Defenses, and Future Directionsby Hao Du, Shang Liu,…
Privacy in Fine-tuning Large Language Models: Attacks, Defenses, and Future Directionsby Hao Du, Shang Liu,…
Federated Learning and RAG Integration: A Scalable Approach for Medical Large Language Modelsby Jincheol Jung,…
A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communitiesby Haotian Ye, Axel Wisiorek,…
FedMetaMed: Federated Meta-Learning for Personalized Medication in Distributed Healthcare Systemsby Jiechao Gao, Yuangang LiFirst submitted…
Beyond Local Sharpness: Communication-Efficient Global Sharpness-aware Minimization for Federated Learningby Debora Caldarola, Pietro Cagnasso, Barbara…
FedPAW: Federated Learning with Personalized Aggregation Weights for Urban Vehicle Speed Predictionby Yuepeng He, Pengzhan…
Federated Progressive Self-Distillation with Logits Calibration for Personalized IIoT Edge Intelligenceby Yingchao Wang, Wenqi NiuFirst…
Artificial Intelligence in Pediatric Echocardiography: Exploring Challenges, Opportunities, and Clinical Applications with Explainable AI and…
Federated Learning for Discrete Optimal Transport with Large Population under Incomplete Informationby Navpreet Kaur, Juntao…
FedDP: Privacy-preserving method based on federated learning for histopathology image segmentationby Liangrui Pan, Mao Huang,…