Unsupervised Domain Adaptation on Sentence Matching Through Self-Supervision
文献类型：期刊论文
| 作者 | Bai, Gui-Rong1,2 ; Liu, Qing-Bin1,2; He, Shi-Zhu2; Liu, Kang1,2; Zhao, Jun1,2
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| 刊名 | JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
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| 出版日期 | 2023-12-01 |
| 卷号 | 38期号:6页码:1237-1249 |
| 关键词 | unsupervised domain adaptation sentence matching self-supervision |
| ISSN号 | 1000-9000 |
| DOI | 10.1007/s11390-022-1479-0 |
| 通讯作者 | He, Shi-Zhu(shizhu.he@nlpr.ia.ac.cn) |
| 英文摘要 | Although neural approaches have yielded state-of-the-art results in the sentence matching task, their performance inevitably drops dramatically when applied to unseen domains. To tackle this cross-domain challenge, we address unsupervised domain adaptation on sentence matching, in which the goal is to have good performance on a target domain with only unlabeled target domain data as well as labeled source domain data. Specifically, we propose to perform self-supervised tasks to achieve it. Different from previous unsupervised domain adaptation methods, self-supervision can not only flexibly suit the characteristics of sentence matching with a special design, but also be much easier to optimize. When training, each self-supervised task is performed on both domains simultaneously in an easy-to-hard curriculum, which gradually brings the two domains closer together along the direction relevant to the task. As a result, the classifier trained on the source domain is able to generalize to the unlabeled target domain. In total, we present three types of self-supervised tasks and the results demonstrate their superiority. In addition, we further study the performance of different usages of self-supervised tasks, which would inspire how to effectively utilize self-supervision for cross-domain scenarios. |
| 资助项目 | National Natural Science Foundation of China[61922085] ; National Natural Science Foundation of China[61976211] ; National Key Research and Development Program of China[2020AAA0106400] ; Key Research Program of the Chinese Academy of Sciences[ZDBS-SSW-JSC006] ; Independent Research Project of the National Laboratory of Pattern Recognition[Z-2018013] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2020138] |
| WOS研究方向 | Computer Science |
| 语种 | 英语 |
| WOS记录号 | WOS:001154653300002 |
| 出版者 | SPRINGER SINGAPORE PTE LTD |
| 资助机构 | National Natural Science Foundation of China ; National Key Research and Development Program of China ; Key Research Program of the Chinese Academy of Sciences ; Independent Research Project of the National Laboratory of Pattern Recognition ; Youth Innovation Promotion Association of Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/55530]  |
| 专题 | 复杂系统认知与决策实验室 |
| 通讯作者 | He, Shi-Zhu |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bai, Gui-Rong,Liu, Qing-Bin,He, Shi-Zhu,et al. Unsupervised Domain Adaptation on Sentence Matching Through Self-Supervision[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2023,38(6):1237-1249. |
| APA | Bai, Gui-Rong,Liu, Qing-Bin,He, Shi-Zhu,Liu, Kang,&Zhao, Jun.(2023).Unsupervised Domain Adaptation on Sentence Matching Through Self-Supervision.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,38(6),1237-1249. |
| MLA | Bai, Gui-Rong,et al."Unsupervised Domain Adaptation on Sentence Matching Through Self-Supervision".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 38.6(2023):1237-1249. |
入库方式： OAI收割
来源：自动化研究所
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