Abstract
This paper describes the Tokyo Tech and AIST system in the GenChal 2022 shared task, which is the first shared task of feedback comment generation. We adopted five methods: data cleaning, fine-tuning pre-trained models, correcting errors in learners’ sentences, appending a correcting operation, and filtering out irrelevant outputs. Our system achieved F1 = 43.4 on the test dataset.- Anthology ID:
- 2023.inlg-genchal.11
- Volume:
- Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges
- Month:
- September
- Year:
- 2023
- Address:
- Prague, Czechia
- Editor:
- Simon Mille
- Venues:
- INLG | SIGDIAL
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 74–78
- Language:
- URL:
- https://aclanthology.org/2023.inlg-genchal.11
- DOI:
- Cite (ACL):
- Shota Koyama, Hiroya Takamura, and Naoaki Okazaki. 2023. The Tokyo Tech and AIST System at the GenChal 2022 Shared Task on Feedback Comment Generation. In Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges, pages 74–78, Prague, Czechia. Association for Computational Linguistics.
- Cite (Informal):
- The Tokyo Tech and AIST System at the GenChal 2022 Shared Task on Feedback Comment Generation (Koyama et al., INLG-SIGDIAL 2023)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2023.inlg-genchal.11.pdf