10 citations · 33 across the 16 of their papers we have counts for
7 papers · 1 filter
Improving Word Sense Disambiguation in Neural Machine Translation with Salient Document Context
Elijah Rippeth, Marine Carpuat, Kevin Duh +1
Lexical ambiguity is a challenging and pervasive problem in machine translation (\mt). We introduce a simple and scalable approach to resolve translation ambiguity by incorporating…
Identifying Context-Dependent Translations for Evaluation Set Production
Rachel Wicks, Matt Post
A major impediment to the transition to context-aware machine translation is the absence of good evaluation metrics and test sets. Sentences that require context to be translated c…
SLIDE: Reference-free Evaluation for Machine Translation using a Sliding Document Window
Vikas Raunak, Tom Kocmi, Matt Post
Reference-based metrics that operate at the sentence-level typically outperform quality estimation metrics, which have access only to the source and system output. This is unsurpri…
SOTASTREAM: A Streaming Approach to Machine Translation Training
Matt Post, Thamme Gowda, Roman Grundkiewicz +3
Many machine translation toolkits make use of a data preparation step wherein raw data is transformed into a tensor format that can be used directly by the trainer. This preparatio…
Do GPTs Produce Less Literal Translations?
Vikas Raunak, Arul Menezes, Matt Post +1
Large Language Models (LLMs) such as GPT-3 have emerged as general-purpose language models capable of addressing many natural language generation or understanding tasks. On the tas…
Multilingual Pixel Representations for Translation and Effective Cross-lingual Transfer
Elizabeth Salesky, Neha Verma, Philipp Koehn +1
We introduce and demonstrate how to effectively train multilingual machine translation models with pixel representations. We experiment with two different data settings with a vari…