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

2022-11-30 · SemEval (NAACL) 2022 7 · Yaqian Han, Yekun Chai, Shuohuan Wang, Yu Sun, Hongyi Huang, Guanghao Chen, Yitong Xu, Yang Yang

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.

📄 PDF Abstract BibTeX arXiv:2211.16883

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Tasks

Multi-Label Classification MUlTI-LABEL-ClASSIFICATION Natural Language Understanding Sarcasm DetectionSentence

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LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification

2020-05-07 · SEMEVAL 2020 · Erfan Ghadery, Marie-Francine Moens

This paper presents our system entitled `LIIR' for SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2). We have participated in sub-task A for English, Danish, Greek, Ara…

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SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis

2022-10-03 · Jiaxin Pei, Vítor Silva, Maarten Bos, Yozon Liu 외

We propose MINT, a new Multilingual INTimacy analysis dataset covering 13,372 tweets in 10 languages including English, French, Spanish, Italian, Portuguese, Korean, Dutch, Chinese, Hindi, and Arabic. We benchmarked a li…

ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social Media

2020-12-01 · SEMEVAL 2020 · Sabit Hassan, Younes Samih, Hamdy Mubarak, Ahmed Abdelali

This paper describes the systems submitted by the Arabic Language Technology group (ALT) at SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media. We focus on sub-task A (Offensive Language…

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KS@LTH at SemEval-2020 Task 12: Fine-tuning Multi- and Monolingual Transformer Models for Offensive Language Detection

2020-12-01 · SEMEVAL 2020 · Kasper Socha

This paper describes the KS@LTH system for SemEval-2020 Task 12 OffensEval2: Multilingual Offensive Language Identification in Social Media. We compare mono- and multilingual models based on fine-tuning pre-trained trans…

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FII\_CROSS at SemEval-2021 Task 2: Multilingual and Cross-lingual Word-in-Context Disambiguation

2021-08-01 · SEMEVAL 2021 · Ciprian Bodnar, Andrada Tapuc, Cosmin Pintilie, Daniela Gifu 외

This paper presents a word-in-context disambiguation system. The task focuses on capturing the polysemous nature of words in a multilingual and cross-lingual setting, without considering a strict inventory of word meanin…

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