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cs.CL2025
FedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models
Chuan Li, Qianyi Zhao, Fengran Mo +1
Enhancing LLM reasoning in federated settings is nontrivial due to stringent computational, communication, and privacy constraints, especially in healthcare, where clinically conse…
cs.CL2024
FedMCP: Parameter-Efficient Federated Learning with Model-Contrastive Personalization
Qianyi Zhao, Chen Qu, Cen Chen +2
With increasing concerns and regulations on data privacy, fine-tuning pretrained language models (PLMs) in federated learning (FL) has become a common paradigm for NLP tasks. Despi…