Papers by Petur Ragnarsson

1 papers
Byte-Level Grammatical Error Correction Using Synthetic and Curated Corpora (2023.acl-long)

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Challenge: Spelling mistakes due to typos and rushed writing, nonstandard punctuation and spelling, and grammatical and stylistic issues are common to almost everyone who writes any kind of text.
Approach: They propose to use a common subword unit vocabulary and byte-level encoding to fine tune two subword-level models and one byte level model on hand-corrected error corpora.
Outcome: The proposed model improves accuracy for spelling and grammatical errors and more complex errors.

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