  Large Language Models (LLMs) have recently demonstrated remarkable
capabilities in natural language processing tasks and beyond. This success of
LLMs has led to a large influx of research contributions in this direction.
These works encompass diverse topics such as architectural innovations, better
training strategies, context length improvements, fine-tuning, multi-modal
LLMs, robotics, datasets, benchmarking, efficiency, and more. With the rapid
development of techniques and regular breakthroughs in LLM research, it has
become considerably challenging to perceive the bigger picture of the advances
in this direction. Considering the rapidly emerging plethora of literature on
LLMs, it is imperative that the research community is able to benefit from a
concise yet comprehensive overview of the recent developments in this field.
This article provides an overview of the existing literature on a broad range
of LLM-related concepts. Our self-contained comprehensive overview of LLMs
discusses relevant background concepts along with covering the advanced topics
at the frontier of research in LLMs. This review article is intended to not
only provide a systematic survey but also a quick comprehensive reference for
the researchers and practitioners to draw insights from extensive informative
summaries of the existing works to advance the LLM research.
