Abstract
We present a model and methodology for
learning paraphrastic sentence embeddings
directly from bitext, removing the timeconsuming 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 stateof-the-art baselines.