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Machine Translation On Wmt2014 German English

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BLEU score

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

Modellname	BLEU score	Paper Title	Repository
CMLM+LAT+1 iterations	29.91	Incorporating a Local Translation Mechanism into Non-autoregressive Translation	-
SimCut	34.86	Bi-SimCut: A Simple Strategy for Boosting Neural Machine Translation
CNAT	30.75	Non-Autoregressive Translation by Learning Target Categorical Codes
BiBERT	34.94	BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation
Denoising autoencoders (non-autoregressive)	25.43	Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
NAT +FT + NPD	23.20	Non-Autoregressive Neural Machine Translation
FlowSeq-large (NPD n = 15)	27.71	FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
Mega	33.12	Mega: Moving Average Equipped Gated Attention
SMT + iterative backtranslation (unsupervised)	17.43	Unsupervised Statistical Machine Translation
FlowSeq-large	25.4	FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
Bi-SimCut	35.15	Bi-SimCut: A Simple Strategy for Boosting Neural Machine Translation
FlowSeq-base	23.36	FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
MAT+Knee	31.9	Wide-minima Density Hypothesis and the Explore-Exploit Learning Rate Schedule
CMLM+LAT+4 iterations	32.04	Incorporating a Local Translation Mechanism into Non-autoregressive Translation	-
FlowSeq-large (IWD n=15)	27.16	FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow
FlowSeq-large (NPD n = 30)	28.29	FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow

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