Bilateral Multi-Perspective Matching for Natural Language Sentences
Table 1: Ablation studies on the dev set.
['Models', 'Accuracy']
Second, to check the effectiveness of bilateral matching, we build two ablation models to matching sentences in only a single direction: 1) “Only P→Q” which only matches P against Q; 2) Comparing the two ablation models with the “Full Model”, we can observe that single direction matching hurts the performance for about 1 percent. Therefore, matching sentences in two directions is really necessary for acquiring better performance. Third, we evaluate the effectiveness of different matching strategies. To this end, we construct four ablation models (w/o Full-Matching, w/o Maxpooling-Matching, w/o Attentive-Matching, w/o Max-Attentive-Matching) by eliminating a matching strategy at each time. We can see that eliminating any of the matching strategies would hurt the performance significantly.