Papers with GEC base systems

1 papers
System Combination via Quality Estimation for Grammatical Error Correction (2023.emnlp-main)

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Challenge: Existing quality estimation models are not good enough to distinguish good corrections from bad ones, resulting in low F0.5 scores when used for system combination.
Approach: They propose a new quality estimation model that gives a better estimate of the quality of a corrected sentence.
Outcome: The proposed model outperforms the state-of-the-art on the CoNLL-2014 and BEA-2019 test sets, and achieves the highest F0.5 scores published to date.

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