Subword-augmented Embedding for Cloze Reading Comprehension
Table 4: Accuracy on PD and CFT datasets. Results of AS Reader and CAS Reader are from [Cui et al.2016].
['Model', 'PD Valid', 'PD Test', 'CFT Test-human']
Since there is no training set for CFT dataset, our model is trained on PD training set. Note that the CFT dataset is harder for the machine to answer because the test set is further processed by human evaluation, and may not be accordance with the pattern of PD dataset. As we see that, our SAW Reader significantly outperforms the CAS Reader in all types of testing, with improvements of 7.0% on PD and 8.8% on CFT test sets, respectively. Although the domain and topic of PD and CFT datasets are quite different, the results indicate that our model also works effectively for out-of-domain learning.