Several categories of Large Language Models (LLMs): A Short Survey
Saurabh Pahune Manoj Chandrasekharan
Large Language Models(LLMs)have become effective tools for natural language
processing and have been used in many different fields. This essay offers a
succinct summary of various LLM subcategories. The survey emphasizes recent
developments and efforts made for various LLM kinds, including task-based
financial LLMs, multilingual language LLMs, biomedical and clinical LLMs,
vision language LLMs, and code language models. The survey gives a general
summary of the methods, attributes, datasets, transformer models, and
comparison metrics applied in each category of LLMs. Furthermore, it highlights
unresolved problems in the field of developing chatbots and virtual assistants,
such as boosting natural language processing, enhancing chatbot intelligence,
and resolving moral and legal dilemmas. The purpose of this study is to provide
readers, developers, academics, and users interested in LLM-based chatbots and
virtual intelligent assistant technologies with useful information and future
directions.