Search Results for author:
Found 6 papers, 2 papers with code
ParBLEU: Augmenting Metrics with Automatic Paraphrases for the WMT’20 Metrics Shared Task
We describe parBLEU, parCHRF++, and parESIM, which augment baseline metrics with automatically generated paraphrases produced by PRISM (Thompson and Post, 2020a), a multilingual neural machine translation system.
Multilingual Neural Machine Translation With the Right Amount of Sharing
Large multilingual Transformer-based machine translation models have had a pivotal role in making translation systems available for hundreds of languages with good zero-shot translation performance.
MTee: Open Machine Translation Platform for Estonian Government
We present the MTee project - a research initiative funded via an Estonian public procurement to develop machine translation technology that is open-source and free of charge.
Extremely low-resource machine translation for closely related languages
An effective method to improve extremely low-resource neural machine translation is multilingual training, which can be improved by leveraging monolingual data to create synthetic bilingual corpora using the back-translation method.
Low-Resource Neural Machine Translation
Transfer Learning
+1
A Study in Improving BLEU Reference Coverage with Diverse Automatic Paraphrasing
We investigate a long-perceived shortcoming in the typical use of BLEU: its reliance on a single reference.
Correlated daily time series and forecasting in the M4 competition
We participated in the M4 competition for time series forecasting and describe here our methods for forecasting daily time series.
