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Unsupervised Machine Translation On Wmt2016
Metrics
BLEU
Results
Performance results of various models on this benchmark
| Paper Title | Repository | ||
|---|---|---|---|
| GPT-3 175B (Few-Shot) | 29.7 | Language Models are Few-Shot Learners | |
| MASS (6-layer Transformer) | 28.3 | MASS: Masked Sequence to Sequence Pre-training for Language Generation | |
| SMT + NMT (tuning and joint refinement) | 26.9 | An Effective Approach to Unsupervised Machine Translation | |
| MLM pretraining for encoder and decoder | 26.4 | Cross-lingual Language Model Pretraining | |
| SMT as posterior regularization | 21.7 | Unsupervised Neural Machine Translation with SMT as Posterior Regularization | |
| PBSMT + NMT | 20.2 | Phrase-Based & Neural Unsupervised Machine Translation | |
| Synthetic bilingual data init | 20.0 | Unsupervised Neural Machine Translation Initialized by Unsupervised Statistical Machine Translation | - |
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