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

arXiv 1711.05732 ↗First posted 15 Nov 2017cs.CLcited by 44

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Abstract (arXiv)

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.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Nov 2017.

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Citing papers per year: 2021: 22; 2022: 13; 2023: 9.

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  1. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
  2. 2021Generating Datasets with Pretrained Language Modelscited by 192
  3. 2022A Review on Language Models as Knowledge Basescited by 156
  4. 2021NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentationcited by 72
  5. 2021Text Detoxification using Large Pre-trained Neural Modelscited by 52
  6. 2021Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Explorationcited by 44
  7. 2021Source and Target Bidirectional Knowledge Distillation for End-to-end Speech Translationcited by 27
  8. 2021Few-shot Controllable Style Transfer for Low-Resource Multilingual Settingscited by 20
  9. 2021Paraphrastic Representations at Scalecited by 19
  10. 2021XtremeDistilTransformers: Task Transfer for Task-agnostic Distillationcited by 18
  11. 2021BiSECT: Learning to Split and Rephrase Sentences with Bitextscited by 18
  12. 2022Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Frameworkcited by 18
32 more
  1. 2022Data Augmentation with Paraphrase Generation and Entity Extraction for Multimodal Dialogue Systemcited by 16
  2. 2021Disentangling Representations of Text by Masking Transformerscited by 15
  3. 2021An Unsupervised Method for Building Sentence Simplification Corpora in Multiple Languagescited by 14
  4. 2021Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Qualitycited by 13
  5. 2021IGA : An Intent-Guided Authoring Assistantcited by 12
  6. 2023Paraphrase Detection: Human vs. Machine Contentcited by 12
  7. 2021Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reorderingcited by 10
  8. 2023Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extractioncited by 8
  9. 2021Improving Automated Evaluation of Open Domain Dialog via Diverse Reference Augmentationcited by 6
  10. 2022Training Naturalized Semantic Parsers with Very Little Datacited by 6
  11. 2022ParaCotta: Synthetic Multilingual Paraphrase Corpora from the Most Diverse Translation Sample Paircited by 6
  12. 2021From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Surveycited by 5
  13. 2022Onception: Active Learning with Expert Advice for Real World Machine Translationcited by 5
  14. 2022Principled Paraphrase Generation with Parallel Corporacited by 5
  15. 2022Exploring Diversity in Back Translation for Low-Resource Machine Translationcited by 5
  16. 2023Bridging Continuous and Discrete Spaces: Interpretable Sentence Representation Learning via Compositional Operationscited by 5
  17. 2023Semantic Similarity Loss for Neural Source Code Summarizationcited by 5
  18. 2021Generative Pretraining for Paraphrase Evaluationcited by 4
  19. 2021Mitigating Data Scarceness through Data Synthesis, Augmentation and Curriculum for Abstractive Summarizationcited by 4
  20. 2022Unsupervised Sentence Textual Similarity with Compositional Phrase Semanticscited by 4
  21. 2022Revision for Concision: A Constrained Paraphrase Generation Taskcited by 4
  22. 2023The Daunting Dilemma with Sentence Encoders: Success on Standard Benchmarks, Failure in Capturing Basic Semantic Propertiescited by 4
  23. 2021Exploiting Twitter as Source of Large Corpora of Weakly Similar Pairs for Semantic Sentence Embeddingscited by 3
  24. 2022AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Modelscited by 3
  25. 2023Syntactically Robust Training on Partially-Observed Data for Open Information Extractioncited by 3
  26. 2021Diversifying Neural Text Generation with Part-of-Speech Guided Softmax and Samplingcited by 2
  27. 2021Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputscited by 2
  28. 2022Conciseness: An Overlooked Language Taskcited by 1
  29. 2023Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generationcited by 1
  30. 2023Paraphrase Acquisition from Image Captionscited by 1
  31. 2022Natural Language Sentence Generation from API Specificationscited by 0
  32. 2023Sentence Simplification Using Paraphrase Corpus for Initializationcited by 0