@inproceedings{qianwen-etal-2024-ji,
title = "基于大模型数据增强的作文流畅性评价方法",
author = "Qianwen, Peng and
Yanzipeng, Gao and
Xiaoqing, Li and
Fanke, Min and
Mingrui, Li and
Zhichun, Wang and
Tianyun, Liu",
editor = "Lin, Hongfei and
Tan, Hongye and
Li, Bin",
booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
month = jul,
year = "2024",
address = "Taiyuan, China",
publisher = "Chinese Information Processing Society of China",
url = "https://aclanthology.org/2024.ccl-3.33/",
pages = "294--301",
language = "zho",
abstract = "{\textquotedblleft}CCL2024-Eval任 务7为 中 小 学 生 作 文 流 畅 性 评 价 (Chinese Essay Fluency Evalua-tion,CEFE),该任务定义了三项重要且富有挑战性的问题,包括中小学作文病句类型识别、中小学作文病句改写、以及中小学作文流畅性评级。本队伍参加了评测任务7的三项子任务,分别获得了45.19、43.90和45.84的得分。本报告详细介绍本队伍在三个子任务上采用的技术方法,并对评测结果进行分析。{\textquotedblright}"
}
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<abstract>“CCL2024-Eval任 务7为 中 小 学 生 作 文 流 畅 性 评 价 (Chinese Essay Fluency Evalua-tion,CEFE),该任务定义了三项重要且富有挑战性的问题,包括中小学作文病句类型识别、中小学作文病句改写、以及中小学作文流畅性评级。本队伍参加了评测任务7的三项子任务,分别获得了45.19、43.90和45.84的得分。本报告详细介绍本队伍在三个子任务上采用的技术方法,并对评测结果进行分析。”</abstract>
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%0 Conference Proceedings
%T 基于大模型数据增强的作文流畅性评价方法
%A Qianwen, Peng
%A Yanzipeng, Gao
%A Xiaoqing, Li
%A Fanke, Min
%A Mingrui, Li
%A Zhichun, Wang
%A Tianyun, Liu
%Y Lin, Hongfei
%Y Tan, Hongye
%Y Li, Bin
%S Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
%D 2024
%8 July
%I Chinese Information Processing Society of China
%C Taiyuan, China
%G zho
%F qianwen-etal-2024-ji
%X “CCL2024-Eval任 务7为 中 小 学 生 作 文 流 畅 性 评 价 (Chinese Essay Fluency Evalua-tion,CEFE),该任务定义了三项重要且富有挑战性的问题,包括中小学作文病句类型识别、中小学作文病句改写、以及中小学作文流畅性评级。本队伍参加了评测任务7的三项子任务,分别获得了45.19、43.90和45.84的得分。本报告详细介绍本队伍在三个子任务上采用的技术方法,并对评测结果进行分析。”
%U https://aclanthology.org/2024.ccl-3.33/
%P 294-301
Markdown (Informal)
[基于大模型数据增强的作文流畅性评价方法](https://aclanthology.org/2024.ccl-3.33/) (Qianwen et al., CCL 2024)
ACL
- Peng Qianwen, Gao Yanzipeng, Li Xiaoqing, Min Fanke, Li Mingrui, Wang Zhichun, and Liu Tianyun. 2024. 基于大模型数据增强的作文流畅性评价方法. In Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations), pages 294–301, Taiyuan, China. Chinese Information Processing Society of China.