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Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the
  Ugly
v1v2 (latest)

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

4 October 2023
Herbert Woisetschläger
Alexander Erben
Shiqiang Wang
R. Mayer
Hans-Arno Jacobsen
    FedML
ArXiv (abs)PDFHTML

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

13 / 13 papers shown
Title
FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE
FLAME: Towards Federated Fine-Tuning Large Language Models Through Adaptive SMoE
Khiem Le
Tuan V. Tran
Ting Hua
Nitesh Chawla
MoE
193
0
0
19 Jun 2025
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
FedRPCA: Enhancing Federated LoRA Aggregation Using Robust PCA
Divyansh Jhunjhunwala
Arian Raje
Madan Ravi Ganesh
Chaithanya Kumar Mummadi
Chaoqun Dong
Jiawei Zhou
Wan-Yi Lin
Gauri Joshi
Zhenzhen Li
211
0
0
01 Jun 2025
FDA-Opt: Communication-Efficient Federated Fine-Tuning of Language Models
FDA-Opt: Communication-Efficient Federated Fine-Tuning of Language Models
Michail Theologitis
V. Samoladas
Antonios Deligiannakis
355
0
0
07 May 2025
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
Yang Liu
Bingjie Yan
Tianyuan Zou
Jianqing Zhang
Zixuan Gu
...
Jiajian Li
Xiaozhou Ye
Ye Ouyang
Qiang Yang
Yanzhe Zhang
ALM
938
2
0
24 Apr 2025
TaskComplexity: A Dataset for Task Complexity Classification with
  In-Context Learning, FLAN-T5 and GPT-4o Benchmarks
TaskComplexity: A Dataset for Task Complexity Classification with In-Context Learning, FLAN-T5 and GPT-4o Benchmarks
Areeg Fahad Rasheed
M. Zarkoosh
Safa F. Abbas
Sana Sabah Al-Azzawi
108
5
0
30 Sep 2024
Federated Large Language Models: Current Progress and Future Directions
Federated Large Language Models: Current Progress and Future Directions
Yuhang Yao
Jianyi Zhang
Junda Wu
Chengkai Huang
Yu Xia
...
Ang Li
L. Yao
Julian McAuley
Yiran Chen
Carlee Joe-Wong
FedMLAIFin
333
16
0
24 Sep 2024
Mobile Edge Intelligence for Large Language Models: A Contemporary Survey
Mobile Edge Intelligence for Large Language Models: A Contemporary Survey
Guanqiao Qu
Qiyuan Chen
Wei Wei
Zheng Lin
Xianhao Chen
Kaibin Huang
445
132
0
09 Jul 2024
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6GIEEE Communications Magazine (IEEE Commun. Mag.), 2024
Xiaoxue Yu
Xingfu Yi
Rongpeng Li
Fei Wang
Chenghui Peng
Zhifeng Zhao
Honggang Zhang
210
3
0
06 May 2024
Training Machine Learning models at the Edge: A Survey
Training Machine Learning models at the Edge: A Survey
Aymen Rayane Khouas
Mohamed Reda Bouadjenek
Hakim Hacid
Sunil Aryal
330
20
0
05 Mar 2024
A Survey on Efficient Federated Learning Methods for Foundation Model
  Training
A Survey on Efficient Federated Learning Methods for Foundation Model TrainingInternational Joint Conference on Artificial Intelligence (IJCAI), 2024
Herbert Woisetschläger
Alexander Isenko
Shiqiang Wang
R. Mayer
Hans-Arno Jacobsen
FedML
218
37
0
09 Jan 2024
Federated Full-Parameter Tuning of Billion-Sized Language Models with
  Communication Cost under 18 Kilobytes
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
201
53
0
11 Dec 2023
Green Edge AI: A Contemporary Survey
Green Edge AI: A Contemporary SurveyProceedings of the IEEE (Proc. IEEE), 2023
Yuyi Mao
X. Yu
Kaibin Huang
Ying-Jun Angela Zhang
Jun Zhang
310
49
0
01 Dec 2023
Towards Open Federated Learning Platforms: Survey and Vision from
  Technical and Legal Perspectives
Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives
Moming Duan
Qinbin Li
Linshan Jiang
Bingsheng He
FedML
349
5
0
05 Jul 2023
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