Before revision:  Training an ordinary neural sequence model on a dataset augmented with recombined and resampled examples significantly improves generalization in two language processing problems---instruction following (SCAN) and morphological analysis ( Sigmorphon 2018) ---where our approach  enables learning of new constructions and tenses from as few as eight initial examples.
After revision:  Training an ordinary neural sequence model on a dataset augmented with recombined and resampled examples significantly improves generalization in two language processing problems---instruction following (SCAN) and morphological analysis ( Sigmorphon 2018) -- where R enables learning of new constructions and tenses from as few as eight initial examples.