Knowledge Commons of Institute of Automation,CAS
Pre-trained Language Model Based Active Learning for Sentence Matching | |
Bai GR(白桂荣)1,2; He SZ(何世柱)1,2; Liu K(刘康)1,2; Zhao J(赵军)1,2 | |
2020 | |
会议名称 | COLING2020 |
页码 | 1495-1504 |
会议日期 | 2020 |
会议地点 | 线上 |
出版地 | Barcelona |
出版者 | International Committee on Computational Linguistics |
摘要 | Active learning is able to significantly reduce the annotation cost for data-driven techniques. However, previous active learning approaches for natural language processing mainly depend on the entropy-based uncertainty criterion, and ignore the characteristics of natural language. In this paper, we propose a pre-trained language model based active learning approach for sentence matching. Differing from previous active learning, it can provide linguistic criteria to measure instances and help select more efficient instances for annotation. Experiments demonstrate our approach can achieve greater accuracy with fewer labeled training instances. |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48869 |
专题 | 多模态人工智能系统全国重点实验室_自然语言处理 |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学人工智能学院 |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Bai GR,He SZ,Liu K,et al. Pre-trained Language Model Based Active Learning for Sentence Matching[C]. Barcelona:International Committee on Computational Linguistics,2020:1495-1504. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
coling2020.pdf(594KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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