Version 1
: Received: 3 October 2024 / Approved: 3 October 2024 / Online: 3 October 2024 (10:57:52 CEST)
How to cite:
Gresham, D. Exploring and Evaluating Large Language Model Survey Paper Categories. Preprints2024, 2024100226. https://doi.org/10.20944/preprints202410.0226.v1
Gresham, D. Exploring and Evaluating Large Language Model Survey Paper Categories. Preprints 2024, 2024100226. https://doi.org/10.20944/preprints202410.0226.v1
Gresham, D. Exploring and Evaluating Large Language Model Survey Paper Categories. Preprints2024, 2024100226. https://doi.org/10.20944/preprints202410.0226.v1
APA Style
Gresham, D. (2024). Exploring and Evaluating Large Language Model Survey Paper Categories. Preprints. https://doi.org/10.20944/preprints202410.0226.v1
Chicago/Turabian Style
Gresham, D. 2024 "Exploring and Evaluating Large Language Model Survey Paper Categories" Preprints. https://doi.org/10.20944/preprints202410.0226.v1
Abstract
In February of 2024, Dr. Jun Zhuang and Dr. Casey Kennington published a paper (Zhuang and Kennington, 2024) in which they classified large language model (LLM) survey papers into different taxonomies utilizing graph learning. In this paper, I evaluate the dataset they created and used and propose that in its current state, there is not enough samples to classify other survey papers into specific categories.
Keywords
machine learning; data science; large language models; graph representation learning
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
