SubmissionNumber#=%=#27
FinalPaperTitle#=%=#iML at SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials with LLM Based Ensemble Inferencing
ShortPaperTitle#=%=#
NumberOfPages#=%=#5
CopyrightSigned#=%=#Abbas Akkasi
JobTitle#==#
Organization#==#School Of Computer Science, Carleton University, Ottawa, Canada
Abstract#==#We engaged in this shared task2 at SemEval-2024, employing a diverse set of solutions, with a particular emphasis on leveraging a Large Language Model (LLM) based  zero-shot inference approach to address the challenge.
Author{1}{Firstname}#=%=#Abbas
Author{1}{Lastname}#=%=#Akkasi
Author{1}{Username}#=%=#akkasi
Author{1}{Email}#=%=#abbasakkasi@cunet.carleton.ca
Author{1}{Affiliation}#=%=#School of Computer Science, Carleton University
Author{2}{Firstname}#=%=#Adnan
Author{2}{Lastname}#=%=#Khan
Author{2}{Email}#=%=#adnankhan5@cmail.carleton.ca
Author{2}{Affiliation}#=%=#School of Computer Science, Carleton university
Author{3}{Firstname}#=%=#Mai A.
Author{3}{Lastname}#=%=#Shaaban
Author{3}{Email}#=%=#mai.kassem@mbzuai.ac.ae
Author{3}{Affiliation}#=%=#Mohamed bin Zayed University of Artificial Intelligence
Author{4}{Firstname}#=%=#Majid
Author{4}{Lastname}#=%=#Komeili
Author{4}{Email}#=%=#majidkomeili@cunet.carleton.ca
Author{4}{Affiliation}#=%=#School of Computer Science, Carleton University
Author{5}{Firstname}#=%=#Mohammad
Author{5}{Lastname}#=%=#Yaqub
Author{5}{Email}#=%=#mohammad.yaqub@mbzuai.ac.ae
Author{5}{Affiliation}#=%=#Mohamed bin Zayed University of Artificial Intelligence

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