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cs.LG2026★ 1 cited
A Survey on Federated Fine-tuning of Large Language Models
Yebo Wu, Chunlin Tian, Jingguang Li +8
Large Language Models (LLMs) have demonstrated impressive success across various tasks. Integrating LLMs with Federated Learning (FL), a paradigm known as FedLLM, offers a promisin…
cs.LG2025
Learning Like Humans: Resource-Efficient Federated Fine-Tuning through Cognitive Developmental Stages
Yebo Wu, Jingguang Li, Zhijiang Guo +1
Federated fine-tuning enables Large Language Models (LLMs) to adapt to downstream tasks while preserving data privacy, but its resource-intensive nature limits deployment on edge d…
cs.LG2024
Heterogeneity-Aware Coordination for Federated Learning via Stitching Pre-trained blocks
Shichen Zhan, Yebo Wu, Chunlin Tian +2
Federated learning (FL) coordinates multiple devices to collaboratively train a shared model while preserving data privacy. However, large memory footprint and high energy consumpt…