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cs.LG2026
Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning
Nuocheng Yang, Yechen He, Sihua Wang +3
As large language models (LLMs) are increasingly deployed at the network edge to provide pervasive generative AI services, decentralized federated learning (DFL) provides a vital m…
cs.LG2026
Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
Nuocheng Yang, Sihua Wang, Ouwen Huan +3
Decentralized federated learning (DFL) based on low-rank adaptation (LoRA) enables mobile devices with multi-task datasets to collaboratively fine-tune a large language model (LLM)…
cs.LG2026
A Secure and Private Distributed Bayesian Federated Learning Design
Nuocheng Yang, Sihua Wang, Zhaohui Yang +3
Distributed Federated Learning (DFL) enables decentralized model training across large-scale systems without a central parameter server. However, DFL faces three critical challenge…