Exploratory Data Analysis and Modeling of Large Language Model Survey Papers

Data analysis

Abstract

In this report, we present an exploratory data analysis of a dataset containing survey papers related to large language models (LLMs). The analysis is performed using a combination of data manipulation techniques with Pandas, visualized with Matplotlib, and preprocessed using Sklearn for modeling purposes. Key insights regarding trends, popular research topics, and metadata of the surveyed papers are discussed. This analysis aims to provide a better understanding of the recent advancements and research directions in the field of LLMs, contributing to the broader study of artificial intelligence. Our report includes data exploration, modeling performance, and a discussion of the results, offering a clear methodology for analyzing academic datasets.