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Sarcasm is a form of figurative language where the intended meaning of asentence differs from its literal meaning. This poses a serious challenge toseveral Natural Language Processing (NLP) applications such as SentimentAnalysis, Opinion Mining, and Author Profiling. In this paper, we present ourparticipating system to the intended sarcasm detection task in English andArabic languages. Our system\footnote{The source code of our system isavailable at \url{https://github.com/AbdelkaderMH/iSarcasmEval}} consists ofthree deep learning-based models leveraging two existing pre-trained languagemodels for Arabic and English. We have participated in all sub-tasks. Ourofficial submissions achieve the best performance on sub-task A for Arabiclanguage and rank second in sub-task B. For sub-task C, our system is ranked7th and 11th on Arabic and English datasets, respectively.

CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic