AMTA Best Thesis Award Abstract: Overcoming Vocabulary Challenges in Natural Language Processing

Elizabeth Salesky


Abstract
This thesis addresses the vocabulary bottleneck in machine translation and other natural language processing applications, exploring more robust and flexible representations of text and their impact on translation quality and cross-lingual generalization. This volume includes a short summary of the thesis; the full thesis is available separately.
Anthology ID:
2026.amta-research.1
Volume:
Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track)
Month:
August
Year:
2026
Address:
Québec City, Canada
Editors:
Eleftheria Briakou, Jeremy Gwinnup, Shivali Goel
Venue:
AMTA
SIG:
Publisher:
Association for Machine Translation in the Americas
Note:
Pages:
1–2
Language:
URL:
https://aclanthology.org/2026.amta-research.1/
DOI:
Bibkey:
Cite (ACL):
Elizabeth Salesky. 2026. AMTA Best Thesis Award Abstract: Overcoming Vocabulary Challenges in Natural Language Processing. In Proceedings of the 17th Conference of the Association for Machine Translation in the Americas (Volume 1: Research Track), pages 1–2, Québec City, Canada. Association for Machine Translation in the Americas.
Cite (Informal):
AMTA Best Thesis Award Abstract: Overcoming Vocabulary Challenges in Natural Language Processing (Salesky, AMTA 2026)
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PDF:
https://aclanthology.org/2026.amta-research.1.pdf