Papers with CGEC task

2 papers
Rethinking the Roles of Large Language Models in Chinese Grammatical Error Correction (2025.acl-industry)

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Challenge: Recent studies have shown that Large Language Models’ performance as correctors on Chinese Grammatical Error Correction (CGEC) remains unsatisfactory due to the challenging nature of the task.
Approach: They propose a training framework EXAM that uses LLMs as explainers to enhance CGEC small models and a novel evaluation method SEE that utilizes LLM as evaluators to bring more reasonable evaluations.
Outcome: The proposed methods improve the performance of LLMs on Chinese Grammatical Error Correction (CGEC) task.
From Spelling to Grammar: A New Framework for Chinese Grammatical Error Correction (2022.findings-emnlp)

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Challenge: Chinese Grammatical Error Correction (CGEC) aims to generate correct sentences from erroneous sequences.
Approach: They propose a zero-shot approach for spelling error correction that is simple but effective . they propose auxiliary task to predict POS sequence of target sentence .
Outcome: The proposed framework achieves 42.11 F-0.5 on the English GEC dataset outperforms the previous state-of-the-art by a wide margin of 1.30 points.

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