PALI-NLP at SemEval-2022 Task 6: iSarcasmEval- Fine-tuning the Pre-trained Model for Detecting Intended Sarcasm
Year: 2022
Type: conference-paper
Abstract: This paper describes the method we utilized in the SemEval-2022 Task 6 iSarcasmEval: Intended Sarcasm Detection In English and Arabic.Our system has achieved 1st in Sub-taskB, which is to identify the categories of intended sarcasm.The proposed system integrates multiple BERT-based, RoBERTa-based and BERTweet-based models with finetuning.In this task, our contribution is listed as follow: 1) we reveal several large pre-trained models' performance on tasks coping with the tweetlike text.2) Our methods prove that we can still achieve excellent results in this particular task without a complex classifier adopting some proper training method.3) we found there is a hierarchical relationship of sarcasm types in this task.
Authors: Xiyang Du, Dou Hu, Jin Zhi, Lianxin Jiang, Xiaofeng Shi
Institution: Ping An (China)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4287889069