12 citations · 13 across the 7 of their papers we have counts for
6 papers · 1 filter
PyMarian: Fast Neural Machine Translation and Evaluation in Python
Thamme Gowda, Roman Grundkiewicz, Elijah Rippeth +2
The deep learning language of choice these days is Python; measured by factors such as available libraries and technical support, it is hard to beat. At the same time, software wri…
Recovering document annotations for sentence-level bitext
Rachel Wicks, Matt Post, Philipp Koehn
Data availability limits the scope of any given task. In machine translation, historical models were incapable of handling longer contexts, so the lack of document-level datasets w…
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…
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…
Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network
Keisuke Sakaguchi, Kevin Duh, Matt Post +1
Language processing mechanism by humans is generally more robust than computers. The Cmabrigde Uinervtisy (Cambridge University) effect from the psycholinguistics literature has de…