67 citations · 67 across the 2 of their papers we have counts for
3 papers
cs.CL2021
Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits
Julia Kreutzer, David Vilar, Artem Sokolov
Training data for machine translation (MT) is often sourced from a multitude of large corpora that are multi-faceted in nature, e.g. containing contents from multiple domains or di…
cs.CL2020★ 67 cited
The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020
Tobias Domhan, Michael Denkowski, David Vilar +3
We present Sockeye 2, a modernized and streamlined version of the Sockeye neural machine translation (NMT) toolkit. New features include a simplified code base through the use of M…
cs.CL2018
Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation
Matt Post, David Vilar
The end-to-end nature of neural machine translation (NMT) removes many ways of manually guiding the translation process that were available in older paradigms. Recent work, however…