Knowledge Commons of Institute of Automation,CAS
Using Pre-trained Language Model to Enhance Active Learning for Sentence Matching | |
Bai, Guirong1,2![]() ![]() ![]() ![]() | |
发表期刊 | ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
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ISSN | 2375-4699 |
2022-03-01 | |
卷号 | 21期号:2页码:19 |
摘要 | Active learning is an effective method to substantially alleviate the problem of expensive annotation cost for data-driven models. Recently, pre-trained language models have been demonstrated to be powerful for learning language representations. In this article, we demonstrate that the pre-trained language model can also utilize its learned textual characteristics to enrich criteria of active learning. Specifically, we provide extra textual criteria with the pre-trained language model to measure instances, including noise, coverage, and diversity. With these extra textual criteria, we can select more efficient instances for annotation and obtain better results. We conduct experiments on both English and Chinese sentence matching datasets. The experimental results show that the proposed active learning approach can be enhanced by the pre-trained language model and obtain better performance. |
关键词 | Sentence matching active learning pre-trained language model |
DOI | 10.1145/3480937 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[61976211] ; National Natural Science Foundation of China[61922085] ; Beijing Academy of Artifcial Intelligence[BAAI2019QN0301] ; Key Research Program of the Chinese Academy of Sciences[ZDBS-SSW-JSC006] ; independent research project of the National Laboratory of Pattern Recognition, China ; Youth Innovation Promotion Association CAS, China |
项目资助者 | National Natural Science Foundation of China ; Beijing Academy of Artifcial Intelligence ; Key Research Program of the Chinese Academy of Sciences ; independent research project of the National Laboratory of Pattern Recognition, China ; Youth Innovation Promotion Association CAS, China |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000775466500021 |
出版者 | ASSOC COMPUTING MACHINERY |
七大方向——子方向分类 | 自然语言处理 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48196 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
通讯作者 | Bai, Guirong |
作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Bai, Guirong,He, Shizhu,Liu, Kang,et al. Using Pre-trained Language Model to Enhance Active Learning for Sentence Matching[J]. ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,2022,21(2):19. |
APA | Bai, Guirong,He, Shizhu,Liu, Kang,&Zhao, Jun.(2022).Using Pre-trained Language Model to Enhance Active Learning for Sentence Matching.ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,21(2),19. |
MLA | Bai, Guirong,et al."Using Pre-trained Language Model to Enhance Active Learning for Sentence Matching".ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 21.2(2022):19. |
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