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Scored Systems

System Submitter System Notes Constraint Run Notes BLEU BLEU-cased TER BEER 2.0 CharactTER
uedin-nmt-ensemble  (Details) rsennrich
University of Edinburgh
BPE neural MT system with monolingual training data (back-translated). ensemble of 4 L2R and 4 R2L models. yes

28.9

28.3

0.612

0.592

0.518

UniMelb-NMT-Transformer-BT  (Details) vhoang
The University of Melbourne, Australia
NMT with Transformer architecture (medium size, 4 heads + 4 encoder/decoder layers) enhanced with WMT'16 back-translation data. (decoding with single best system) yes

27.8

27.3

0.612

0.585

0.540

en_de_transformer_test  (Details) hpulfc
hpulfc
transformer base system yes

27.7

27.2

0.627

0.583

0.538

en_de_transformer_test  (Details) hpulfc
hpulfc
transformer base system yes

27.7

27.1

0.626

0.584

0.540

LMU-nmt-reranked-wmt17-en-de  (Details) Matthias.Huck
LMU Munich
NMT, single model plus r2l reranking, linguistically motivated target word segmentation yes

27.9

27.1

0.618

0.583

0.538

SYSTRAN-single  (Details) jmcrego
SYSTRAN
OpenNMT + BPE + backtranslated monolingual data + hyperspecialization yes

28.0

26.7

0.611

0.580

0.542

xmu-ensemble  (Details) Zhixing Tan
Xiamen University
ensemble 4 models + bpe + backtranslation yes

27.2

26.7

0.622

0.580

0.540

lium-nmt-backtrans-ensemble-ftuned  (Details) ozancaglayan
LIUM - Le Mans University
Ensemble of 2 backtranslated augmented finetuned-NMT trained with nmtpy yes

27.2

26.6

0.633

0.581

0.544

LMU-nmt-single-wmt17-en-de  (Details) Matthias.Huck
LMU Munich
NMT, single model (contrastive), linguistically motivated target word segmentation yes

27.3

26.6

0.626

0.579

0.544

uedin-nmt-single  (Details) rsennrich
University of Edinburgh
BPE neural MT system with monolingual training data (back-translated). single model. (contrastive) yes

27.2

26.6

0.627

0.582

0.539

fbk-nmt-combination  (Details) Mattia Di Gangi
AppTek
OpenNMT + bpe + backtranslations + system combination yes

26.9

26.3

0.636

0.574

0.592

KIT-cG-mA-single  (Details) thanhleha
KIT
yes

26.9

26.3

0.631

0.578

0.547

xmu-single-backtrans  (Details) Zhixing Tan
Xiamen University
single model on preprocessed data + bpe + backtranslation (contrastive) yes

26.7

26.1

0.628

0.576

0.544

KIT primary  (Details) eunah.cho
KIT
NMT, BPE, rescore using five models yes

26.7

26.1

0.641

0.577

0.546

RWTH NMT   (Details) jtp
RWTH Aachen University
Ensemble of 3 using backtranslated data and BPE yes

26.8

26.0

0.628

failed

failed

KIT correct BT single  (Details) thanhleha
KIT
yes

26.5

25.9

0.628

0.577

0.568

xmu-single  (Details) Zhixing Tan
Xiamen University
single model on preprocessed data + bpe (contrastive) yes

26.3

25.7

0.639

0.570

0.562

uedin-nmt-2016  (Details) rsennrich
University of Edinburgh
single system of WMT16 (uedin-nmt-single). Contrastive. yes

25.5

24.9

0.649

0.571

0.559

fbk-nmt-single  (Details) Mattia Di Gangi
AppTek
OpenNMT + bpe + backtranslations (contrastive) yes

25.3

24.8

0.644

0.569

0.576

C-3MA  (Details) mphi
University of Tartu
Nematus + filtered monolingual back-translated data + NE forcing + ngram deduplication yes NeuralMonkey + filtered monolingual back-translated data + NE forcing + ngram deduplication

23.2

22.7

0.669

0.553

0.598

Moses Phrase-Based, word clusters  (Details) jhu-smt
Johns Hopkins University
Moses, use of word clusters. Preliminary run (full run may not finish): use of word clusters in OSM, LM. yes Moses phrase-based, word cluster LM

22.2

21.6

0.709

0.557

0.596

TALP-UPC  (Details) cescolano
TALP-UPC
Character to character NMT system with additional monolingual training data (backtranslated) and rescoring using the inverse language pair model. yes Character to character NMT system with extra corpus and rescoring using the inverse language pair model.

21.9

21.2

0.685

0.548

0.587

BaseNematusEnDe  (Details) m4t1ss
Tilde
yes This should be right

21.4

21.0

0.706

0.544

0.599

ParFDA  (Details) bicici
en-de ParFDA Moses phrase-based SMT system yes en-de (after the deadline)

19.1

18.5

0.749

0.533

0.647

PROMT Rule-based  (Details) Alex Molchanov
PROMT LLC
no

17.0

16.6

0.752

0.527

0.602