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Unsupervised Paraphrasing of Multiword Expressions

arXiv 2306.01443 ↗First posted 2 Jun 2023cs.CL cs.AI cs.LGcited by 0

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Abstract (arXiv)

We propose an unsupervised approach to paraphrasing multiword expressions (MWEs) in context. Our model employs only monolingual corpus data and pre-trained language models (without fine-tuning), and does not make use of any external resources such as dictionaries. We evaluate our method on the SemEval 2022 idiomatic semantic text similarity task, and show that it outperforms all unsupervised systems and rivals supervised systems.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 24 of its 49 references that are in the map. First posted on arXiv 2 Jun 2023.

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References · 24

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  4. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  5. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  6. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,935
  7. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,790
  8. 2020mT5: A massively multilingual pre-trained text-to-text transformercited by 1,818
  9. 2017SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluationcited by 1,001
  10. 2019SpanBERT: Improving Pre-training by Representing and Predicting Spanscited by 834
  11. 2019CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Datacited by 548
  12. 2020AdapterHub: A Framework for Adapting Transformerscited by 444
12 more
  1. 2020A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languagescited by 131
  2. 2022SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embeddingcited by 36
  3. 2021AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Modelscited by 27
  4. 2020How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Contextcited by 26
  5. 2019BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performancecited by 19
  6. 2021Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Qualitycited by 13
  7. 2022Unsupervised Lexical Substitution with Decontextualised Embeddingscited by 8
  8. 2021Bertinho: Galician BERT Representationscited by 7
  9. 2021Idiomatic Expression Paraphrasing without Strong Supervisioncited by 7
  10. 2022drsphelps at SemEval-2022 Task 2: Learning idiom representations using BERTRAMcited by 5
  11. 2022Chinese Idiom Paraphrasingcited by 5
  12. 2022Getting BART to Ride the Idiomatic Train: Learning to Represent Idiomatic Expressionscited by 4

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