Language Graph Distillation for Low-Resource Machine Translation
Table 2: The language pairs improved in the first two iterations of our method. The results demonstrate that our method achieves better accuracy than the +BT and +Forward baseline on the low-resource translation edges in the graph. T indicates iteration step. Av. indicates averaged BLEU scores. Note that, we just demonstrate the preliminary results to verify the effectiveness of our language graph distillation method.
['[ITALIC] T', 'Pair', 'Initial', '+BT', '+Forward', '+Graph']
In this section, we show the preliminary experimental results of the proposed language graph distillation. The third column is the BLEU score obtained by the basic multilingual model (Initial). The forth, five and sixth columns are the results trained with only one-hop back-translation (+BT), only forward distillation (+Forward) and our language graph distillation (+Graph: both forward and backward distillation) respectively. The +BT baseline is obtained by training the selected language pairs with one-hop back-translation data, while the +Forward baseline is obtained by training the selected language pairs with all the forward distillation data.