X-PuDu at SemEval-2022 Task 6: Multilingual Learning for English and Arabic Sarcasm Detection
Not on the map. Why?
Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 14 of its 29 references that are in the map. First posted on arXiv 30 Nov 2022.
Builds on
14 of 29 references.
References · 14
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2018GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understandingcited by 4,854
- 2017Decoupled Weight Decay Regularizationcited by 1,722
- 2021DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharingcited by 1,219
- 2019ERNIE: Enhanced Representation through Knowledge Integrationcited by 301
- 2020ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corporacited by 63
- 2019iSarcasm: A Dataset of Intended Sarcasmcited by 39
- 2018Reasoning with Sarcasm by Reading In-betweencited by 38
- 2019A Transformer-based approach to Irony and Sarcasm detectioncited by 28
- 2016Modelling Context with User Embeddings for Sarcasm Detection in Social Mediacited by 26
- 2020Sarcasm Detection in Tweets with BERT and GloVe Embeddingscited by 8
Built on by
Citing papers per year: 2024: 1; 2025: 1.
2 papers.