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Simple and Effective Paraphrastic Similarity from Parallel Translations

2019-09-30 · ACL 2019 7 · John Wieting, Kevin Gimpel, Graham Neubig, Taylor Berg-Kirkpatrick

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.

📄 PDF Abstract BibTeX arXiv:1909.13872

Code (4)

acl-org/reviewer-paper-matching pytorch
jwcmu/paraphrastic-sentence-embeddings pytorch
jwieting/paraphrastic-representations-at-scale pytorch
jwieting/simple-and-effective-paraphrastic-similarity pytorch

Tasks

SentenceSentence Embeddings

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