Attentive Pooling Networks
Table 3: Accuracy of different systems for InsuranceQA
['[BOLD] System', '[BOLD] Dev', '[BOLD] Test1', '[BOLD] Test2']
The results are in terms of accuracy, which is equivalent to precision at top one. On the bottom part of this table, we can see that AP-CNN outperforms QA-CNN by a large margin in both test sets, as well as in the dev set. AP-biLSTM also outperforms the QA-biLSTM in all the three sets. AP-CNN and AP-biLSTM have similar performance. Both AP-CNN and AP-biLSTM outperform the state-of-the-art systems.