@inproceedings{ma-etal-2023-system,
title = "System Report for {CCL}23-Eval Task 7: {C}hinese Grammatical Error Diagnosis Based on Model Fusion",
author = "Ma, Yanmei and
Wang, Laiqi and
Chen, Zhenghua and
Zhou, Yanran and
Han, Ya and
Zhang, Jie",
editor = "Sun, Maosong and
Qin, Bing and
Qiu, Xipeng and
Jiang, Jing and
Han, Xianpei",
booktitle = "Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
month = aug,
year = "2023",
address = "Harbin, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2023.ccl-3.28",
pages = "250--261",
abstract = "{``}The purpose of the Chinese Grammatical Error Diagnosis task is to identify the positions andtypes of grammar errors in Chinese texts. In Track 2 of CCL2023-CLTC, Chinese grammarerrors are classified into four categories: Redundant Words, Missing Words, Word Selection, andWord Ordering Errors. We conducted data filtering, model research, and model fine-tuning insequence. Then, we performed weighted fusion of models based on perplexity calculations andintroduced various post-processing strategies. As a result, the performance of the model on thetest set, measured by COM, reached 49.12.{''}",
language = "English",
}
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<abstract>“The purpose of the Chinese Grammatical Error Diagnosis task is to identify the positions andtypes of grammar errors in Chinese texts. In Track 2 of CCL2023-CLTC, Chinese grammarerrors are classified into four categories: Redundant Words, Missing Words, Word Selection, andWord Ordering Errors. We conducted data filtering, model research, and model fine-tuning insequence. Then, we performed weighted fusion of models based on perplexity calculations andintroduced various post-processing strategies. As a result, the performance of the model on thetest set, measured by COM, reached 49.12.”</abstract>
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%0 Conference Proceedings
%T System Report for CCL23-Eval Task 7: Chinese Grammatical Error Diagnosis Based on Model Fusion
%A Ma, Yanmei
%A Wang, Laiqi
%A Chen, Zhenghua
%A Zhou, Yanran
%A Han, Ya
%A Zhang, Jie
%Y Sun, Maosong
%Y Qin, Bing
%Y Qiu, Xipeng
%Y Jiang, Jing
%Y Han, Xianpei
%S Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2023
%8 August
%I Chinese Information Processing Society of China
%C Harbin, China
%G English
%F ma-etal-2023-system
%X “The purpose of the Chinese Grammatical Error Diagnosis task is to identify the positions andtypes of grammar errors in Chinese texts. In Track 2 of CCL2023-CLTC, Chinese grammarerrors are classified into four categories: Redundant Words, Missing Words, Word Selection, andWord Ordering Errors. We conducted data filtering, model research, and model fine-tuning insequence. Then, we performed weighted fusion of models based on perplexity calculations andintroduced various post-processing strategies. As a result, the performance of the model on thetest set, measured by COM, reached 49.12.”
%U https://aclanthology.org/2023.ccl-3.28
%P 250-261
Markdown (Informal)
[System Report for CCL23-Eval Task 7: Chinese Grammatical Error Diagnosis Based on Model Fusion](https://aclanthology.org/2023.ccl-3.28) (Ma et al., CCL 2023)
ACL