SubmissionNumber#=%=#103
FinalPaperTitle#=%=#UMUTeam at SemEval-2024 Task 8: Combining Transformers and Syntax Features for Machine-Generated Text Detection
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#José Antonio García Díaz
JobTitle#==#
Organization#==#Universidad de Murcia
Abstract#==#These working notes describe the UMUTeam's participation in Task 8 of SemEval-2024 entitled "Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text Detection". This shared task aims at identifying machine-generated text in order to mitigate its potential misuse. This shared task is divided into three subtasks: Subtask A, a binary classification task to determine whether a given full-text was written by a human or generated by a machine; Subtask B, a multi-class classification problem to determine, given a full-text, who generated it. It can be written by a human or generated by a specific language model; and Subtask C, mixed human-machine text recognition. We participated in Subtask B, using an approach based on fine-tuning a pre-trained model, such as RoBERTa, combined with syntactic features of the texts. Our system placed 23rd out of a total of 77 participants, with a score of 75.350\%, outperforming the baseline.
Author{1}{Firstname}#=%=#ronghao
Author{1}{Lastname}#=%=#pan
Author{1}{Username}#=%=#ronghaopan
Author{1}{Email}#=%=#ronghao.pan@um.es
Author{1}{Affiliation}#=%=#Universidad de Murcia
Author{2}{Firstname}#=%=#José Antonio
Author{2}{Lastname}#=%=#García-Díaz
Author{2}{Username}#=%=#joseagd
Author{2}{Email}#=%=#joseantonio.garcia8@um.es
Author{2}{Affiliation}#=%=#Universidad de Murcia
Author{3}{Firstname}#=%=#Pedro José
Author{3}{Lastname}#=%=#Vivancos-Vicente
Author{3}{Email}#=%=#pedro.vivancos@vocali.net
Author{3}{Affiliation}#=%=#VÓCALI Sistemas Inteligentes S.L
Author{4}{Firstname}#=%=#Rafael
Author{4}{Lastname}#=%=#Valencia-García
Author{4}{Username}#=%=#valencia
Author{4}{Email}#=%=#valencia@um.es
Author{4}{Affiliation}#=%=#Universidad de Murcia

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