Papers by Sudhanshu Kasewa

1 papers
Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection (D18-1)

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Challenge: grammatical error correction is a labor-intensive task that requires large amounts of training data.
Approach: They propose to use a human-annotated corpus of human-generated grammatical errors to generate a synthetic model.
Outcome: The proposed method outperforms the current state of the art in grammatical error correction . human annotators achieve 39.39 F1 scores, suggesting the model generates mostly human-like instances .

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