Abstract
This paper presents the systems and approaches of the Arizonans team for the SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis. We finetune the Multilingual RoBERTa model trained with about 200M tweets, XLM-T. Our final model ranked 9th out of 45 overall, 13th in seen languages, and 8th in unseen languages.- Anthology ID:
- 2023.semeval-1.230
- Volume:
- Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Editors:
- Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1656–1659
- Language:
- URL:
- https://preview.aclanthology.org/icon-24-ingestion/2023.semeval-1.230/
- DOI:
- 10.18653/v1/2023.semeval-1.230
- Cite (ACL):
- Nimet Beyza Bozdag, Tugay Bilgis, and Steven Bethard. 2023. Arizonans at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis with XLM-T. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1656–1659, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Arizonans at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis with XLM-T (Bozdag et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/icon-24-ingestion/2023.semeval-1.230.pdf