Comparison and Analysis of Large Language Models Based on Transformer

Yingying Chang

2024

Abstract

In the quickly developing field of Natural Language Processing (NLP), this study delves into the significance and evolution of Transformer-based Large Language Models (LLMs), which play a pivotal role in advancing linguistic analysis and applications. The research aims to leverage the capabilities of these models to enhance interpretation in medical image classification. This objective is pursued through a structured approach that involves training and evaluating LLMs on the PathMNIST dataset. The methodology includes data normalization, augmentation, and segmentation, followed by fine-tuning on the specialized dataset to optimize model performance. The conducted research demonstrates the robustness and accuracy of the models in classifying various pathological conditions, indicating a significant improvement in medical diagnostic processes. These findings underscore the potential of LLMs to revolutionize Artificial Intelligence (AI) applications in healthcare, offering substantial enhancements in diagnosis and patient care. Such advancements highlight the real-world implications of augmenting AI's interpretive and analytical capacities, promising significant benefits for medical outcomes.

Paper Citation

in Harvard Style

Chang Y. (2024). Comparison and Analysis of Large Language Models Based on Transformer. In Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-713-9, SciTePress, pages 597-602. DOI: 10.5220/0012960200004508

in Bibtex Style

@conference{emiti24,
author={Yingying Chang},
title={Comparison and Analysis of Large Language Models Based on Transformer},
booktitle={Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2024},
pages={597-602},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012960200004508},
isbn={978-989-758-713-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Comparison and Analysis of Large Language Models Based on Transformer
SN - 978-989-758-713-9
AU - Chang Y.
PY - 2024
SP - 597
EP - 602
DO - 10.5220/0012960200004508
PB - SciTePress