Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation
Table 6: Ablation test (%) of the curriculum learning framework on the DailyDialog dataset with SEQ2SEQ.
['[EMPTY]', 'BLEU', 'Dist-1', 'Dist-2', 'Dist-3', 'Intra-1', 'Intra-2', 'Intra-3', 'Avg', 'Ext', 'Gre', 'Coh', 'Ent-1', 'Ent-2']
When training the model with anti-curriculum learning, i.e., feeding examples to the model in the complex-to-easy manner, we also observe consistent performance decreases, affirming the effectiveness of the easy-to-complex learning manner.