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cs.LG2025
HAFLQ: Heterogeneous Adaptive Federated LoRA Fine-tuned LLM with Quantization
Yang Su, Na Yan, Yansha Deng +2
Federated fine-tuning of pre-trained Large Language Models (LLMs) enables task-specific adaptation across diverse datasets while preserving privacy. However, challenges such as hig…
cs.LG2025
PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts
Yang Su, Na Yan, Yansha Deng +1
Large language models (LLMs) hosted on cloud servers alleviate the computational and storage burdens on local devices but raise privacy concerns due to sensitive data transmission…
cs.LG2025
Federated Fine-Tuning of LLMs: Framework Comparison and Research Directions
Na Yan, Yang Su, Yansha Deng +1
Federated learning (FL) provides a privacy-preserving solution for fine-tuning pre-trained large language models (LLMs) using distributed private datasets, enabling task-specific a…