CERD: A Comprehensive Chinese Rhetoric Dataset for Rhetorical Understanding and Generation in Essays

Nuowei Liu, Xinhao Chen, Hongyi Wu, Changzhi Sun, Man Lan, Yuanbin Wu, Xiaopeng Bai, Shaoguang Mao, Yan Xia


Anthology ID:
2024.findings-emnlp.395
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2024
Month:
November
Year:
2024
Address:
Miami, Florida, USA
Editors:
Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
6744–6759
Language:
URL:
https://aclanthology.org/2024.findings-emnlp.395
DOI:
10.18653/v1/2024.findings-emnlp.395
Bibkey:
Cite (ACL):
Nuowei Liu, Xinhao Chen, Hongyi Wu, Changzhi Sun, Man Lan, Yuanbin Wu, Xiaopeng Bai, Shaoguang Mao, and Yan Xia. 2024. CERD: A Comprehensive Chinese Rhetoric Dataset for Rhetorical Understanding and Generation in Essays. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 6744–6759, Miami, Florida, USA. Association for Computational Linguistics.
Cite (Informal):
CERD: A Comprehensive Chinese Rhetoric Dataset for Rhetorical Understanding and Generation in Essays (Liu et al., Findings 2024)
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PDF:
https://aclanthology.org/2024.findings-emnlp.395.pdf