AUTHOR=Saleh Yasmeen , Abu Talib Manar , Nasir Qassim , Dakalbab Fatima 

TITLE=Evaluating large language models: a systematic review of efficiency, applications, and future directions

JOURNAL=Frontiers in Computer Science

VOLUME=Volume 7 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/computer-science/articles/10.3389/fcomp.2025.1523699

DOI=10.3389/fcomp.2025.1523699

ISSN=2624-9898

ABSTRACT=Large language models, the innovative breakthrough taking the world by storm, have been applied in several fields, such as medicine, education, finance, and law. Moreover, large language models can integrate into those fields through their abilities in natural language processing, text generation, question answering, and several other use cases that benefit human interactions and decision-making. Furthermore, it is imperative to acknowledge the differences involved with large language models beyond their applications by considering aspects such as their types, setups, parameters, and performance. This could help us understand how each large language model could be utilized to its fullest extent for maximum benefit. In this systematic literature review, we explore each of these aspects in depth. Finally, we conclude with insights and future directions for advancing the efficiency and applicability of large language models.