A Federated Fine-Tuning Framework for Large Language Models via Graph Representation Learning and Structural Segmentation

This paper focuses on the efficient fine-tuning of large language models within the federated learning framework. To address the performance bottlenecks caused by multi-source heterogeneity and structural inconsistency, a structure-aware federated fine-tuning method is proposed. The method incorpora...

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Bibliografiske detaljer

Principais autores:	Yuxin Dong, Ruotong Wang, Guiran Liu, Binrong Zhu, Xiaohan Cheng, Zijun Gao, Pengbin Feng
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2025-10-01
Serier:	Mathematics
Fag:	federated learning large language models privacy preservation graph representation learning structure-aware fine-tuning
Online adgang:	https://www.mdpi.com/2227-7390/13/19/3201
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