Abstract
We report on the results of the first ever shared task on feedback comment generation for language learners held as Generation Challenge (GenChal) in INLG 2022, which we call FCG GenChal. Feedback comment generation for language learners is a task where, given a text and a span, a system generates, for the span, an explanatory note that helps the writer (language learner) improve their writing skills. We show how well we can generate feedback comments with present techniques. We also shed light on the task properties and the difficulties in this task, with insights into the task including data development, evaluation, and comparisons of generation systems.- Anthology ID:
- 2023.inlg-genchal.7
- 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:
- 45–52
- Language:
- URL:
- https://aclanthology.org/2023.inlg-genchal.7
- DOI:
- Cite (ACL):
- Ryo Nagata, Masato Hagiwara, Kazuaki Hanawa, and Masato Mita. 2023. A Report on FCG GenChal 2022: Shared Task on Feedback Comment Generation for Language Learners. In Proceedings of the 16th International Natural Language Generation Conference: Generation Challenges, pages 45–52, Prague, Czechia. Association for Computational Linguistics.
- Cite (Informal):
- A Report on FCG GenChal 2022: Shared Task on Feedback Comment Generation for Language Learners (Nagata et al., INLG-SIGDIAL 2023)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/2023.inlg-genchal.7.pdf