Survey Trends and Taxonomy Distribution in Large Language Models

Abstract

In this project, we analyze trends in survey papers on Large Language Models (LLMs) and explore the distribution of proposed taxonomy categories. We use Python code to process the data, perform trend analysis over time, and examine the frequency of taxonomy categories. Additionally, we build a feature matrix to combine various features of the data and apply preprocessing for future predictive tasks.