Abstract
In this thesis, we focus on detecting fine-grained semantic divergences—subtle meaning differences in sentences that overlap in content—to improve machine and human translation understanding.- Anthology ID:
- 2024.amta-research.1
- Volume:
- Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
- Month:
- September
- Year:
- 2024
- Address:
- Chicago, USA
- Editors:
- Rebecca Knowles, Akiko Eriguchi, Shivali Goel
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 1–3
- Language:
- URL:
- https://preview.aclanthology.org/info-author-pages/2024.amta-research.1/
- DOI:
- Cite (ACL):
- Eleftheria Briakou. 2024. AMTA Best Thesis Award Abstract: Detecting Fine-Grained Semantic Divergences to Improve Translation Understanding Across Languages. In Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pages 1–3, Chicago, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- AMTA Best Thesis Award Abstract: Detecting Fine-Grained Semantic Divergences to Improve Translation Understanding Across Languages (Briakou, AMTA 2024)
- PDF:
- https://preview.aclanthology.org/info-author-pages/2024.amta-research.1.pdf