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Hairong Lv

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Review Open access Sep 2026

Federated Fine-Tuning of Large Language Models on Resource-Constrained Clients: Technical Approaches, Resource Costs, and Applicability

Federated fine-tuning adapts language models to distributed data and is widely adopted as a privacy-preserving alternative to centralized training, yet constrained clients must still store model weights and training states, execute updates, and communicate with a server. This review examines four composable routes---pa...

Yun-Heng Shen, Xiao Liu, Yang Yang et al. · 0 citations
Preprint Aug 2026

Training-Free Token-Level Steering for LLM Personalized Co-Writing

This work introduces SteerWrite, a training-free framework designed for personalized co-writing that effectively adapts the base model to specialized domains without gradient updates, with specific designs tailored to small datasets.

Wenhao Mao, Chengbin Hou, Wei-Xiao Wang et al. · 0 citations

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