A Review on Large Language Models: Architectures, Applications, Open Issues and Challenges

TITLE	A Review on Large Language Models: Architectures, Applications, Open Issues and Challenges
ABSTRACT	Large Language Models (LLMs) recently demonstrated extraordinary capability, including natural language processing (NLP), language translation, text generation, question answering, etc. Moreover, LLMs are a new and essential part of computerized language processing, having the ability to understand complex verbal patterns and generate coherent and appropriate replies for the situation. Though this success of LLMs has prompted a substantial increase in research contributions, rapid growth has made it difficult to understand the overall impact of these improvements. Since a lot of new research on LLMs is coming out quickly, it is getting tough to get an overview of all of them in a short note. This article thoroughly overviews LLMs, including their history, architectures, transformers, resources, training methods, applications, impacts, challenges, etc. This paper begins by discussing the fundamental concepts of LLMs with its traditional pipeline of the LLM training phase. It then provides an overview of the existing works, the history of LLMs, their evolution over time, the architecture of transformers in LLMs, the different resources of LLMs, and the different training methods that have been used to train them. It also demonstrated the datasets utilized in the studies. The paper discusses the wide range of applications of LLMs, including biomedical and healthcare, education, social, business, and agriculture.
AUTHOR	Suchithra M, Shivaram P, Shrinivas S Pai Department of MCA, CMR Institute of Technology, Bengaluru, India
PUBLICATION DATE	2025-09-08
VOLUME	12
DOI	DOI:10.15680/IJARETY.2025.1204074
PDF	74_A Review on Large Language Models Architectures, Applications, Open Issues and Challenges.pdf
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