Abstract
This paper describes our system used for SemEval 2022 Task 6: iSarcasmEval: Intended Sarcasm Detection in English and Arabic. We participated in all subtasks based on only English datasets. Pre-trained Language Models (PLMs) have become a de-facto approach for most natural language processing tasks. In our work, we evaluate the performance of these models for identifying sarcasm. For Subtask A and Subtask B, we used simple finetuning on PLMs. For Subtask C, we propose a Siamese network architecture trained using a combination of cross-entropy and distance-maximisation loss. Our model was ranked 7th in Subtask B, 8th in Subtask C (English), and performed well in Subtask A (English). In our work, we also present the comparative performance of different PLMs for each Subtask.- Anthology ID:
- 2022.semeval-1.143
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1018–1024
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.143
- DOI:
- 10.18653/v1/2022.semeval-1.143
- Cite (ACL):
- Mayukh Sharma, Ilanthenral Kandasamy, and Vasantha W B. 2022. R2D2 at SemEval-2022 Task 6: Are language models sarcastic enough? Finetuning pre-trained language models to identify sarcasm. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1018–1024, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- R2D2 at SemEval-2022 Task 6: Are language models sarcastic enough? Finetuning pre-trained language models to identify sarcasm (Sharma et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/naacl24-info/2022.semeval-1.143.pdf
- Data
- iSarcasm, iSarcasmEval