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    <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.</abstract>
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%0 Conference Proceedings
%T AMTA Best Thesis Award Abstract: Detecting Fine-Grained Semantic Divergences to Improve Translation Understanding Across Languages
%A Briakou, Eleftheria
%Y Knowles, Rebecca
%Y Eriguchi, Akiko
%Y Goel, Shivali
%S Proceedings of the 16th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
%D 2024
%8 September
%I Association for Machine Translation in the Americas
%C Chicago, USA
%F briakou-2024-amta
%X 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.
%U https://aclanthology.org/2024.amta-research.1/
%P 1-3

Markdown (Informal)

[AMTA Best Thesis Award Abstract: Detecting Fine-Grained Semantic Divergences to Improve Translation Understanding Across Languages](https://aclanthology.org/2024.amta-research.1/) (Briakou, AMTA 2024)

• AMTA Best Thesis Award Abstract: Detecting Fine-Grained Semantic Divergences to Improve Translation Understanding Across Languages (Briakou, AMTA 2024)

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.