A Comprehensive Review of Large Language Models: Capabilities, Limitations, and Ethical Considerations

Abstract

Large Language Models (LLMs) like GPT, BERT, and LLaMA have transformed natural language processing by achieving human-like text generation and understanding. This paper reviews the architecture, training methodologies, and applications of LLMs across industries. We discuss key challenges such as bias, misinformation, and ethical concerns surrounding their use. Additionally, we explore techniques to improve efficiency, interpretability, and alignment with human values. The paper concludes with future directions for making LLMs more responsible and reliable.