Dual Learning for Semi-Supervised Natural Language Understanding
TABLE VIII: Ablation studies of the dual learning method.
['[BOLD] Method', '[BOLD] SNIPS (5%) Slot F1', '[BOLD] SNIPS (5%) Intent Acc']
From the results of “(-) w/o unlabeled sentences” and “(-) w/o unexpressed semantic forms” rows, we can find that unexpressed semantic forms are more important, which is consistent with the findings in the ablation studies of the dual pseudo-labeling method. It may facilitate semi-supervised NLU, since semantic forms are well-structured and could be easily synthesized under domain knowledge. The last two rows show that two kinds of rewards are essential, while the validity rewards impact more on the slot F1 score.