SubmissionNumber#=%=#177
FinalPaperTitle#=%=#octavianB at SemEval-2024 Task 6: An exploration of humanlike qualities of hallucinated LLM texts
ShortPaperTitle#=%=#
NumberOfPages#=%=#6
CopyrightSigned#=%=#Brodoceanu Octavian
JobTitle#==#
Organization#==#University of Bucharest, Panduri Street, Sector 5, 050663, Bucharest, ROMANIA
Abstract#==#The tested method for detection involves utilizing models, trained for differentiating machine-generated text, in order to distinguish between regular and hallucinated sequences. 
The hypothesis under investigation is that the patterns learned in pretraining will be transferable to the task at hand. 
The rationale is as follows: the training data of the model is human-written text, therefore deviations from the training set could be detected in this manner.
A second method has been added post competition as a further exploration of the dataset involving using the loss of the generation as determined by a pretrained LLM.
Author{1}{Firstname}#=%=#Octavian
Author{1}{Lastname}#=%=#Brodoceanu
Author{1}{Username}#=%=#octavianb
Author{1}{Email}#=%=#octavian.brodoceanu@gmail.com
Author{1}{Affiliation}#=%=#University of Bucharest Faculty of Mathematics and Informatics

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