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X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection

Authors :
Han, Yaqian
Chai, Yekun
Wang, Shuohuan
Sun, Yu
Huang, Hongyi
Chen, Guanghao
Xu, Yitong
Yang, Yang
Publication Year :
2022

Abstract

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.<br />Comment: SemEval-2022 Task 6

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2211.16883
Document Type :
Working Paper