Learning Robust Representations of Text
Table 2: Accuracy under cross-domain evaluation; the best result for each dataset is indicated in bold.
['Train/Test', '[EMPTY]', 'MR/CR', 'CR/MR']
Once again, we see that our regularization method is superior to word-level dropout and the baseline CNN, and the techniques combined do very well, consistent with our findings for synthetic noise.