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Grammar Error Correction using Masked Language Models

Propose a system for grammatical error correction using a masked language model. Introduce a framework consisting of two tasks: tagging, which chooses and arbitrarily reorders a subset of input tokens to keep, and insertion, which infills the missing tokens with another pretrained masked language model.

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Cite this as

Ng et al., Boyd, Rozovskaya and Roth (2024). Dataset: Grammar Error Correction using Masked Language Models. https://doi.org/10.57702/e8gimqyb

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Additional Info

Field	Value
Created	December 16, 2024
Last update	December 16, 2024
Defined In	https://doi.org/10.48550/arXiv.2111.09280
Author	Ng et al.
More Authors	Boyd Rozovskaya and Roth
Homepage	https://aclanthology.org/2014.emnlp-conference.123