# ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations

Source: [ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations](<https://www.sota2.com/research/paper/68fa64401e209131cea0376d>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-25T20:59:11.405Z

Authors: John Wieting, Kevin Gimpel

Published: 2017-11-15T18:59:29.000Z

## Abstract

We describe PARANMT-50M, a dataset of more than 50 million English-English sentential paraphrase pairs. We generated the pairs automatically by using neural machine translation to translate the non-English side of a large parallel corpus, following Wieting et al. (2017). Our hope is that ParaNMT-50M can be a valuable resource for paraphrase generation and can provide a rich source of semantic knowledge to improve downstream natural language understanding tasks. To show its utility, we use ParaNMT-50M to train paraphrastic sentence embeddings that outperform all supervised systems on every SemEval semantic textual similarity competition, in addition to showing how it can be used for paraphrase generation.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

- [Paraphrase Semantic Similarity on Human Evaluation 300 samples (random sample)](<https://www.sota2.com/research/sota/paraphrase-semantic-similarity-on-human-evaluation-300-samples-random-sample.md>): Paraphrase Semantic Similarity; Human Evaluation 300 samples (random sample); Score 3: 28.7.

- [Paraphrase Similarity and Diversity Evaluation on Shared subset of 193,869 source sentences (PARANMT, PARABANK, PARAAMR)](<https://www.sota2.com/research/sota/paraphrase-similarity-and-diversity-evaluation-on-shared-subset-of-193-869-source-sentences-paranmt-parabank-paraamr.md>): Paraphrase Similarity and Diversity Evaluation; Shared subset of 193,869 source sentences (PARANMT, PARABANK, PARAAMR); Semantic Similarity: 84.28.

- [Paraphrase Syntactic Diversity on Human Evaluation 300 samples (random sample)](<https://www.sota2.com/research/sota/paraphrase-syntactic-diversity-on-human-evaluation-300-samples-random-sample.md>): Paraphrase Syntactic Diversity; Human Evaluation 300 samples (random sample); Score 3 (%): 0.167.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1711.05732>)

[PDF](<https://arxiv.org/pdf/1711.05732.pdf>)