no code implementations • 1 Apr 2024 • Parker Riley, Daniel Deutsch, George Foster, Viresh Ratnakar, Ali Dabirmoghaddam, Markus Freitag
Reliable human evaluation is critical to the development of successful natural language generation models, but achieving it is notoriously difficult.
no code implementations • 16 Nov 2022 • David Vilar, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, George Foster
Large language models (LLMs) that have been trained on multilingual but not parallel text exhibit a remarkable ability to translate between languages.
no code implementations • Findings (NAACL) 2022 • Chia-Hsuan Lee, Aditya Siddhant, Viresh Ratnakar, Melvin Johnson
In this paper, we introduce DOCmT5, a multilingual sequence-to-sequence language model pretrained with large scale parallel documents.
Ranked #1 on Document Translation on WMT 2020
3 code implementations • 29 Apr 2021 • Markus Freitag, George Foster, David Grangier, Viresh Ratnakar, Qijun Tan, Wolfgang Macherey
Human evaluation of modern high-quality machine translation systems is a difficult problem, and there is increasing evidence that inadequate evaluation procedures can lead to erroneous conclusions.