SubmissionNumber#=%=#1
FinalPaperTitle#=%=#CUNLP at SemEval-2024 Task 8: Classify Human and AI Generated Text
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#Pranjal Aggarwal
JobTitle#==#
Organization#==#
Abstract#==#This task is a sub-part of SemEval-2024 competition which aims to classify AI vs Human Generated Text. In this paper we have experimented on an approach to automatically classify an artificially generated text and a human written text. With the advent of generative models like GPT-3.5 and GPT-4 it has become increasingly necessary to classify between the two texts due to various applications like detecting plagiarism and in tasks like fake news detection that can heavily impact real world problems, for instance stock manipulation through AI generated news articles. To achieve this, we start by using some basic models like Logistic Regression and move our way up to more complex models like transformers and GPTs for classification. This is a binary classification task where the label 1 represents AI generated text and 0 represents human generated text. The dataset was given in JSON style format which was converted to comma separated file (CSV) for better processing using the pandas library in Python as CSV files provides more readability than JSON format files. Approaches like Bagging Classifier and Voting classifier were also used.
Author{1}{Firstname}#=%=#Pranjal
Author{1}{Lastname}#=%=#Aggarwal
Author{1}{Username}#=%=#pranjalaggarwal
Author{1}{Email}#=%=#pranjalaggarwal1999@gmail.com
Author{1}{Affiliation}#=%=#University of Colorado Boulder
Author{2}{Firstname}#=%=#Deepanshu
Author{2}{Lastname}#=%=#Sachdeva
Author{2}{Email}#=%=#deepanshusachdeva5@gmail.com
Author{2}{Affiliation}#=%=#University of Colorado Boulder

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