Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News
Yuta Koreeda, Ken-ichi Yokote, Hiroaki Ozaki, Atsuki Yamaguchi, Masaya Tsunokake, Yasuhiro Sogawa
Abstract
This paper explains the participation of team Hitachi to SemEval-2023 Task 3 “Detecting the genre, the framing, and the persuasion techniques in online news in a multi-lingual setup.” Based on the multilingual, multi-task nature of the task and the low-resource setting, we investigated different cross-lingual and multi-task strategies for training the pretrained language models. Through extensive experiments, we found that (a) cross-lingual/multi-task training, and (b) collecting an external balanced dataset, can benefit the genre and framing detection. We constructed ensemble models from the results and achieved the highest macro-averaged F1 scores in Italian and Russian genre categorization subtasks.- Anthology ID:
- 2023.semeval-1.237
- Volume:
- Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023)
- Month:
- July
- Year:
- 2023
- Address:
- Toronto, Canada
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1702–1711
- Language:
- URL:
- https://aclanthology.org/2023.semeval-1.237
- DOI:
- Cite (ACL):
- Yuta Koreeda, Ken-ichi Yokote, Hiroaki Ozaki, Atsuki Yamaguchi, Masaya Tsunokake, and Yasuhiro Sogawa. 2023. Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News. In Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 1702–1711, Toronto, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News (Koreeda et al., SemEval 2023)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/2023.semeval-1.237.pdf