9 citations · 32 across the 8 of their papers we have counts for
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cs.LG2023★ 8 cited
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
Zhen Qin, Daoyuan Chen, Bingchen Qian +3
Pre-trained large language models (LLMs) need fine-tuning to improve their responsiveness to natural language instructions. Federated learning offers a way to fine-tune LLMs using…
cs.LG2023★ 9 cited
FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning
Weirui Kuang, Bingchen Qian, Zitao Li +7
LLMs have demonstrated great capabilities in various NLP tasks. Different entities can further improve the performance of those LLMs on their specific downstream tasks by fine-tuni…