  Detecting sarcasm and verbal irony from people's subjective statements is
crucial to understanding their intended meanings and real sentiments and
positions in social scenarios. This paper describes the X-PuDu system that
participated in SemEval-2022 Task 6, iSarcasmEval - Intended Sarcasm Detection
in English and Arabic, which aims at detecting intended sarcasm in various
settings of natural language understanding. Our solution finetunes pre-trained
language models, such as ERNIE-M and DeBERTa, under the multilingual settings
to recognize the irony from Arabic and English texts. Our system ranked second
out of 43, and ninth out of 32 in Task A: one-sentence detection in English and
Arabic; fifth out of 22 in Task B: binary multi-label classification in
English; first out of 16, and fifth out of 13 in Task C: sentence-pair
detection in English and Arabic.
