Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly

4 October 2023

Papers citing "Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly"

6 / 6 papers shown

Title
Communication-Efficient Federated Fine-Tuning of Language Models via Dynamic Update Schedules Michail Theologitis V. Samoladas Antonios Deligiannakis 29 0 0 07 May 2025
Mobile Edge Intelligence for Large Language Models: A Contemporary Survey Guanqiao Qu Qiyuan Chen Wei Wei Zheng Lin Xianhao Chen Kaibin Huang 42 43 0 09 Jul 2024
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G Xiaoxue Yu Xingfu Yi Rongpeng Li Fei Wang Chenghui Peng Zhifeng Zhao Honggang Zhang 64 1 0 06 May 2024
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes Zhen Qin Daoyuan Chen Bingchen Qian Bolin Ding Yaliang Li Shuiguang Deng FedML 32 32 0 11 Dec 2023
ZeRO-Offload: Democratizing Billion-Scale Model Training Jie Ren Samyam Rajbhandari Reza Yazdani Aminabadi Olatunji Ruwase Shuangyang Yang Minjia Zhang Dong Li Yuxiong He MoE 168 414 0 18 Jan 2021
FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He Songze Li Jinhyun So Xiao Zeng Mi Zhang ... Yang Liu Ramesh Raskar Qiang Yang M. Annavaram Salman Avestimehr FedML 168 564 0 27 Jul 2020