ACL Findings2023
Unsupervised Paraphrasing of Multiword Expressions
Takashi Wada, Yuji Matsumoto, Timothy Baldwin, Jey Han Lau
Abstract
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. 1
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Builds on9
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- AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language ModelsHarish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton, Aline VillavicencioEMNLP Findings 2021 · 32 citations
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