Multi-Style Generative Reading Comprehension
Table 5: Performance of our and competing models on the NarrativeQA test set. aSeo et al. (2017); bTay et al. (2018); cBauer et al. (2018); dIndurthi et al. (2018); eHu et al. (2018). fResults on the NarrativeQA validation set.
['Model', 'B-1', 'B-4', 'M', 'R-L']
Does our model achieve state-of-the-art performance? The evaluation scores of the model controlled with the NLG style were low because the two styles are different. Also, our model without multi-style learning (trained with only the NQA style) outperformed the baselines in terms of ROUGE-L. This indicates that our model architecture itself is powerful for natural language understanding in RC.