activity
20162022
most citedIs Neural Machine Translation Ready for Deployment? A Case Study on 30 Translation Directions

150 citations · 162 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL2022★ 4 cited

STable: Table Generation Framework for Encoder-Decoder Models

Michał Pietruszka, Michał Turski, Łukasz Borchmann +5

The output structure of database-like tables, consisting of values structured in horizontal rows and vertical columns identifiable by name, can cover a wide range of NLP tasks. Fol…

cs.CL2021★ 1 cited

Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer

Rafał Powalski, Łukasz Borchmann, Dawid Jurkiewicz +3

We address the challenging problem of Natural Language Comprehension beyond plain-text documents by introducing the TILT neural network architecture which simultaneously learns lay…

cs.CL2020

From Dataset Recycling to Multi-Property Extraction and Beyond

Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2

This paper investigates various Transformer architectures on the WikiReading Information Extraction and Machine Reading Comprehension dataset. The proposed dual-source model outper…

cs.CL2020

On the Multi-Property Extraction and Beyond

Tomasz Dwojak, Michał Pietruszka, Łukasz Borchmann +2

In this paper, we investigate the Dual-source Transformer architecture on the WikiReading information extraction and machine reading comprehension dataset. The proposed model outpe…

cs.CL2018

Fast Neural Machine Translation Implementation

Hieu Hoang, Tomasz Dwojak, Rihards Krislauks +2

This paper describes the submissions to the efficiency track for GPUs at the Workshop for Neural Machine Translation and Generation by members of the University of Edinburgh, Adam…

cs.CL2018

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…

cs.CL2017★ 4 cited

Predicting Target Language CCG Supertags Improves Neural Machine Translation

Maria Nadejde, Siva Reddy, Rico Sennrich +4

Neural machine translation (NMT) models are able to partially learn syntactic information from sequential lexical information. Still, some complex syntactic phenomena such as prepo…

cs.CL2016★ 150 cited

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…

cs.CL2016★ 3 cited

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…