Dynamically Composing Domain-Data Selection with Clean-Data Selection by “Co-Curricular Learning” for Neural Machine Translation
Table 4: Co-curriculum improves either constituent curriculum and no CL, can be close to the true curriculum on noisy data.
['[BOLD] Curriculum', '[BOLD] Test Bleu  [BOLD] IWSLT15', '[BOLD] Test Bleu  [BOLD] WMT14']
Curriculum Bleu comparisons. On Paracrawl, co-curriculum (P7) gives more than +2 Bleu on top of no CL (P1). It improves Cdomain (P7 vs P2) by +1.4 Bleu on IWSLT15 and +1.6 Bleu on WMT14. It is better than either constituent curriculum (P2 or P3), close to the true curriculum (P4).