SubmissionNumber#=%=#164
FinalPaperTitle#=%=#DUTh at SemEval 2024 Task 8: Comparing classic Machine Learning Algorithms and LLM based methods for Multigenerator, Multidomain and Multilingual Machine-Generated Text Detection
ShortPaperTitle#=%=#
NumberOfPages#=%=#7
CopyrightSigned#=%=#Ioannis Maslaris
JobTitle#==#
Organization#==#Database & Information Retrieval research unit,
Department of Electrical & Computer Engineering,
Democritus University of Thrace, Greece
Abstract#==#Text-generative models evolve rapidly nowadays. Although, they are very useful tools for a lot of people, they have also raised concerns for different reasons. This paper presents our work for SemEval2024 Task-8 on 2 out of the 3 subtasks. This shared task aims at finding automatic models for making AI vs. human written text classification easier. Our team, after trying different preprocessing, several Machine Learning algorithms, and some LLMs, ended up with mBERT, XLM-RoBERTa, and BERT for the tasks we submitted. We present both positive and negative methods, so that future researchers are informed about what works and what doesn't.
Author{1}{Firstname}#=%=#Theodora
Author{1}{Lastname}#=%=#Kyriakou
Author{1}{Username}#=%=#dorakyr
Author{1}{Email}#=%=#dorakiriakou10@gmail.com
Author{1}{Affiliation}#=%=#Democritus University of Thrace
Author{2}{Firstname}#=%=#Ioannis
Author{2}{Lastname}#=%=#Maslaris
Author{2}{Username}#=%=#yms1
Author{2}{Email}#=%=#yannismslr@gmail.com
Author{2}{Affiliation}#=%=#Democritus University of Thrace
Author{3}{Firstname}#=%=#Avi
Author{3}{Lastname}#=%=#Arampatzis
Author{3}{Username}#=%=#avi1
Author{3}{Email}#=%=#yannis.maslatis@gmail.com
Author{3}{Affiliation}#=%=#Democritus University of Thrace

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