  We present a model and methodology for learning paraphrastic sentence
embeddings directly from bitext, removing the time-consuming intermediate step
of creating paraphrase corpora. Further, we show that the resulting model can
be applied to cross-lingual tasks where it both outperforms and is orders of
magnitude faster than more complex state-of-the-art baselines.
