Multiple Words to Single Word Associations Using Masked Language Models
Multiple Words to Single Word Associations Using Masked Language Models
复制标题
使用屏蔽语言模型的多个单词到单个单词的关联
DOI：
10.1109/kst57286.2023.10086780
复制
发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Shingo Kuroiwa
中科院分区：
文献类型：
--
作者：
Yuya Soma;Yasuo Horiuchi;Shingo Kuroiwa
In this paper, we examine a word association task that predicts a correct associative word from five stimulus words using Masked Language Models (hereafter referred to as MLMs). For MLMs, we used BERT and gMLP. Since our word association task uses only nouns for both stimulus and associative words, we trained new models by restricting masked tokens to nouns. In our experiment, we input sentences such as “The prefecture associated with Mt. Fuji, Lake Hamana, … and eels is MASK. (富士山,浜名湖,⋯,うなぎから連想する都道府県は MASK です.),” so that MASK outputs an associative word. In the experiments, we also examined adding Japanese quotation marks 「」 before and after the MASK, i.e., 「MASK」. The experiment results showed that the highest percentage of correct answers, 49%, was obtained by adding 「」 before and after the MASK (74% of the correct answers were within the top five words).
DOI：
--
发表时间：
2021-05
期刊：
--
影响因子：
--
作者：
Hanxiao Liu;Zihang Dai;David R. So;Quoc V. Le
通讯作者：
Hanxiao Liu;Zihang Dai;David R. So;Quoc V. Le
提出一种基于关联系统的多词生成关联词的方法
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
Misako;Imono;Eriko;Yoshimura;Seiji;Tsuchiya;Hirokazu;Watabe
通讯作者：
Watabe