Open access
Author
Date
2024Type
- Bachelor Thesis
ETH Bibliography
yes
Altmetrics
Abstract
In this thesis we attempt to utilise large language models (LLMs) to answer networking questions based on router configurations. We establish an approach to ask these questions and evaluate them on the November 2023 preview of OpenAI’s GPT-4 Turbo specifically. Our findings suggest that this LLM performs with varying reliability and requires careful question formulations as well as extensive context to answer correctly. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000661089Publication status
publishedPublisher
ETH ZurichSubject
Large language model; Router configurationOrganisational unit
09477 - Vanbever, Laurent / Vanbever, Laurent
Funding
851809 - From Network Verification to Synthesis: Breaking New Ground in Network Automation (EC)
More
Show all metadata
ETH Bibliography
yes
Altmetrics