Suppr超能文献

可视化机器阅读理解模型中的注意力区域。

Visualizing attention zones in machine reading comprehension models.

机构信息

Research Center for Social Computing and Information Retrieval (SCIR), Harbin Institute of Technology, Harbin 150001, China; State Key Laboratory of Cognitive Intelligence, iFLYTEK Research, Beijing 100083, China.

Research Center for Social Computing and Information Retrieval (SCIR), Harbin Institute of Technology, Harbin 150001, China.

出版信息

STAR Protoc. 2022 Jun 16;3(3):101481. doi: 10.1016/j.xpro.2022.101481. eCollection 2022 Sep 16.

Abstract

The attention mechanism plays an important role in the machine reading comprehension (MRC) model. Here, we describe a pipeline for building an MRC model with a pretrained language model and visualizing the effect of each attention zone in different layers, which can indicate the explainability of the model. With the presented protocol and accompanying code, researchers can easily visualize the relevance of each attention zone in the MRC model. This approach can be generalized to other pretrained language models. For complete details on the use and execution of this protocol, please refer to Cui et al. (2022).

摘要

注意力机制在机器阅读理解 (MRC) 模型中起着重要作用。在这里,我们描述了一个使用预先训练的语言模型构建 MRC 模型的流程,并可视化了不同层中每个注意力区域的效果,这可以表明模型的可解释性。有了本文提出的协议和相关代码,研究人员可以轻松地可视化 MRC 模型中每个注意力区域的相关性。这种方法可以推广到其他预先训练的语言模型。有关此协议的使用和执行的完整详细信息,请参阅 Cui 等人 (2022)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b3c2/9234076/686f71fd69e0/fx1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验