Federated Fine-Tuning of LLMs on the Very Edge: The Good, the Bad, the Ugly-Reference-Cited by-同舟云学术

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

Published:2024-06-09 Issue: Volume:33 Page:39-50
ISSN:
Container-title:Proceedings of the Eighth Workshop on Data Management for End-to-End Machine Learning
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Author:

Woisetschläger Herbert¹^ORCID,Erben Alexander¹^ORCID,Wang Shiqiang²^ORCID,Mayer Ruben³^ORCID,Jacobsen Hans-Arno⁴^ORCID

Affiliation:

1. Technical University of Munich, Munich, Germany

2. IBM T.J. Watson Research Center, Yorktown Heights, United States

3. University of Bayreuth, Bayreuth, Germany

4. University of Toronto, Toronto, Canada

Funder

German Federal Ministry for Economic Affairs and Climate Action

German Research Foundation

Bavarian Ministry of Economic Affairs, Regional Development and Energy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3650203.3663331

Reference51 articles.

1. 3GPP. 4g (lte advanced). https://portal.3gpp.org/desktopmodules/Specifications/SpecificationDetails.aspx?specificationId=2585, 2008.

2. Amazon Web Services (AWS). Amazon AWS p3 instance types. https://aws.amazon.com/ec2/instance-types/p3/, 2023. Accessed: 2023-09-27.

3. Sara Babakniya, Ahmed Elkordy, et al. SLoRA: Federated parameter efficient fine-tuning of language models. In International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS 2023, 2023. URL https://openreview.net/forum?id=06quMTmtRV.

4. ExDRa: Exploratory Data Science on Federated Raw Data

5. Daniel J. Beutel, Taner Topal, Akhil Mathur, Xinchi Qiu, Javier Fernandez-Marques, Yan Gao, Lorenzo Sani, Kwing Hei Li, Titouan Parcollet, Pedro Porto Buarque de Gusmão, and Nicholas D. Lane. Flower: A friendly federated learning research framework, 2020. URL https://arxiv.org/abs/2007.14390.

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