Abstract
Text simplification is the process of rewriting a piece of text using simpler vocabulary and grammatical structure in order to make the text more accessible and understandable for a larger audience. In this paper, we introduce a new text simplification model based on the notion of adaptive teaching using a teacher network and a text generation network. We name this new model Simplification via Adaptive Teaching (SAT). Our proposed model sets a new state-of-the-art performance in terms of standard simplification metrics such as SARI and D-SARI with a significant improvement over the previous state of the art on the D-Wikipedia dataset and the Wiki-Doc benchmark dataset. Moreover, we conduct a human evaluation in terms of text simplicity, correctness, and fluency to substantiate SAT’s performance.- Anthology ID:
- 2024.findings-acl.392
- Volume:
- Findings of the Association for Computational Linguistics: ACL 2024
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6574–6584
- Language:
- URL:
- https://aclanthology.org/2024.findings-acl.392
- DOI:
- 10.18653/v1/2024.findings-acl.392
- Cite (ACL):
- Seyed Ali Bahrainian, Jonathan Dou, and Carsten Eickhoff. 2024. Text Simplification via Adaptive Teaching. In Findings of the Association for Computational Linguistics: ACL 2024, pages 6574–6584, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Text Simplification via Adaptive Teaching (Bahrainian et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.findings-acl.392.pdf