Multilingual Synthetic Question and Answer Generation for Cross-Lingual Reading Comprehension
arxiv(2020)
摘要
We propose a simple method to generate large amounts of multilingual question and answer pairs by a single generative model. These synthetic samples are then applied to augment the available gold multilingual ones to improve the performance of multilingual QA models on target languages. Our approach only requires existence of automatically translated samples from English to the target domain, thus removing the need for human annotations in the target languages. Experimental results show our proposed approach achieves significant gains in a number of multilingual datasets.
更多查看译文
关键词
multilingual synthetic question,answer generation,reading,cross-lingual
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络