566 citations · 824 across the 16 of their papers we have counts for
21 papers
The JHU-Microsoft Submission for WMT21 Quality Estimation Shared Task
Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post +2
This paper presents the JHU-Microsoft joint submission for WMT 2021 quality estimation shared task. We only participate in Task 2 (post-editing effort estimation) of the shared tas…
Levenshtein Training for Word-level Quality Estimation
Shuoyang Ding, Marcin Junczys-Dowmunt, Matt Post +1
We propose a novel scheme to use the Levenshtein Transformer to perform the task of word-level quality estimation. A Levenshtein Transformer is a natural fit for this task: trained…
To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation
Tom Kocmi, Christian Federmann, Roman Grundkiewicz +3
Automatic metrics are commonly used as the exclusive tool for declaring the superiority of one machine translation system's quality over another. The community choice of automatic…
On User Interfaces for Large-Scale Document-Level Human Evaluation of Machine Translation Outputs
Roman Grundkiewicz, Marcin Junczys-Dowmunt, Christian Federmann +1
Recent studies emphasize the need of document context in human evaluation of machine translations, but little research has been done on the impact of user interfaces on annotator p…
The Curious Case of Hallucinations in Neural Machine Translation
Vikas Raunak, Arul Menezes, Marcin Junczys-Dowmunt
In this work, we study hallucinations in Neural Machine Translation (NMT), which lie at an extreme end on the spectrum of NMT pathologies. Firstly, we connect the phenomenon of hal…
Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation
Marcin Junczys-Dowmunt
This paper describes the Microsoft Translator submissions to the WMT19 news translation shared task for English-German. Our main focus is document-level neural machine translation…
Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora
Marcin Junczys-Dowmunt
In this work we introduce dual conditional cross-entropy filtering for noisy parallel data. For each sentence pair of the noisy parallel corpus we compute cross-entropy scores acco…
Microsoft's Submission to the WMT2018 News Translation Task: How I Learned to Stop Worrying and Love the Data
Marcin Junczys-Dowmunt
This paper describes the Microsoft submission to the WMT2018 news translation shared task. We participated in one language direction -- English-German. Our system follows current b…
MS-UEdin Submission to the WMT2018 APE Shared Task: Dual-Source Transformer for Automatic Post-Editing
Marcin Junczys-Dowmunt, Roman Grundkiewicz
This paper describes the Microsoft and University of Edinburgh submission to the Automatic Post-editing shared task at WMT2018. Based on training data and systems from the WMT2017…
Marian: Cost-effective High-Quality Neural Machine Translation in C++
Marcin Junczys-Dowmunt, Kenneth Heafield, Hieu Hoang +2
This paper describes the submissions of the "Marian" team to the WNMT 2018 shared task. We investigate combinations of teacher-student training, low-precision matrix products, auto…
Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation
Roman Grundkiewicz, Marcin Junczys-Dowmunt
We combine two of the most popular approaches to automated Grammatical Error Correction (GEC): GEC based on Statistical Machine Translation (SMT) and GEC based on Neural Machine Tr…
Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Shubha Guha +1
Previously, neural methods in grammatical error correction (GEC) did not reach state-of-the-art results compared to phrase-based statistical machine translation (SMT) baselines. We…
Marian: Fast Neural Machine Translation in C++
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak +9
We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Mar…
Achieving Human Parity on Automatic Chinese to English News Translation
Hany Hassan, Anthony Aue, Chang Chen +21
Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate acr…
Nematus: a Toolkit for Neural Machine Translation
Rico Sennrich, Orhan Firat, Kyunghyun Cho +8
We present Nematus, a toolkit for Neural Machine Translation. The toolkit prioritizes high translation accuracy, usability, and extensibility. Nematus has been used to build top-pe…
Is Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions
Marcin Junczys-Dowmunt, Tomasz Dwojak, Hieu Hoang
In this paper we provide the largest published comparison of translation quality for phrase-based SMT and neural machine translation across 30 translation directions. For ten direc…
Fast, Scalable Phrase-Based SMT Decoding
Hieu Hoang, Nikolay Bogoychev, Lane Schwartz +1
The utilization of statistical machine translation (SMT) has grown enormously over the last decade, many using open-source software developed by the NLP community. As commercial us…
Target-Side Context for Discriminative Models in Statistical Machine Translation
Aleš Tamchyna, Alexander Fraser, Ondřej Bojar +1
Discriminative translation models utilizing source context have been shown to help statistical machine translation performance. We propose a novel extension of this work using targ…
The AMU-UEDIN Submission to the WMT16 News Translation Task: Attention-based NMT Models as Feature Functions in Phrase-based SMT
Marcin Junczys-Dowmunt, Tomasz Dwojak, Rico Sennrich
This paper describes the AMU-UEDIN submissions to the WMT 2016 shared task on news translation. We explore methods of decode-time integration of attention-based neural translation…
Log-linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post-Editing
Marcin Junczys-Dowmunt, Roman Grundkiewicz
This paper describes the submission of the AMU (Adam Mickiewicz University) team to the Automatic Post-Editing (APE) task of WMT 2016. We explore the application of neural translat…
Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction
Marcin Junczys-Dowmunt, Roman Grundkiewicz
In this work, we study parameter tuning towards the M^2 metric, the standard metric for automatic grammar error correction (GEC) tasks. After implementing M^2 as a scorer in the Mo…