@inproceedings{han-etal-2022-x,
title = "{X}-{P}u{D}u at {S}em{E}val-2022 Task 6: Multilingual Learning for {E}nglish and {A}rabic Sarcasm Detection",
author = "Han, Yaqian and
Chai, Yekun and
Wang, Shuohuan and
Sun, Yu and
Huang, Hongyi and
Chen, Guanghao and
Xu, Yitong and
Yang, Yang",
editor = "Emerson, Guy and
Schluter, Natalie and
Stanovsky, Gabriel and
Kumar, Ritesh and
Palmer, Alexis and
Schneider, Nathan and
Singh, Siddharth and
Ratan, Shyam",
booktitle = "Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)",
month = jul,
year = "2022",
address = "Seattle, United States",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.semeval-1.140",
doi = "10.18653/v1/2022.semeval-1.140",
pages = "999--1004",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection
%A Han, Yaqian
%A Chai, Yekun
%A Wang, Shuohuan
%A Sun, Yu
%A Huang, Hongyi
%A Chen, Guanghao
%A Xu, Yitong
%A Yang, Yang
%Y Emerson, Guy
%Y Schluter, Natalie
%Y Stanovsky, Gabriel
%Y Kumar, Ritesh
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y Singh, Siddharth
%Y Ratan, Shyam
%S Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, United States
%F han-etal-2022-x
%X 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.
%R 10.18653/v1/2022.semeval-1.140
%U https://aclanthology.org/2022.semeval-1.140
%U https://doi.org/10.18653/v1/2022.semeval-1.140
%P 999-1004
Markdown (Informal)
[X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection](https://aclanthology.org/2022.semeval-1.140) (Han et al., SemEval 2022)
ACL
- Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun, Hongyi Huang, Guanghao Chen, Yitong Xu, and Yang Yang. 2022. X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 999–1004, Seattle, United States. Association for Computational Linguistics.