  Retrofitting techniques, which inject external resources into word
representations, have compensated the weakness of distributed representations
in semantic and relational knowledge between words. Implicitly retrofitting
word vectors by expansional technique outperforms retrofitting in word
similarity tasks with word vector generalization. In this paper, we propose
unsupervised extrofitting: expansional retrofitting (extrofitting) without
external semantic lexicons. We also propose deep extrofitting: in-depth
stacking of extrofitting and further combinations of extrofitting with
retrofitting. When experimenting with GloVe, we show that our methods
outperform the previous methods on most of word similarity tasks while
requiring only synonyms as an external resource. Lastly, we show the effect of
word vector enrichment on text classification task, as a downstream task.
