FlowSeq-large (NPD n = 30)

Reported on 4 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Natural Language Processing4 results

Machine TranslationonWMT2014 German-English
BLEU score· 2019-09-05
28.29
best: 35.15 (Bi-SimCut)
SOTA
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow arXiv:1909.02480
Machine TranslationonWMT2016 English-Romanian
BLEU score· 2019-09-05
32.35
best: 34.7 (DeLighT)
SOTA
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow arXiv:1909.02480
Machine TranslationonWMT2016 Romanian-English
BLEU score· 2019-09-05
32.91
best: 40.3 (fast-noisy-channel-modeling)
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow arXiv:1909.02480
Machine TranslationonWMT2014 English-German
BLEU score· 2019-09-05
23.64
best: 35.14 (Transformer Cycle (Rev))
FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow arXiv:1909.02480