{"title":"ViMRC - VLSP 2021: Context-Aware Answer Extraction in Vietnamese Question Answering","authors":"Thi-Thu-Hong Le","doi":"10.25073/2588-1086/vnucsce.316","DOIUrl":null,"url":null,"abstract":"MRC is challenging the natural language processing fields; machines automatically have to answer questions based on specific passages for this task. In recent years, machine reading comprehension (MRC) has received much attention; many articles have been written about this task. However, most of those articles only develop models in two main languages, English and Chinese. In this article, we propose to apply a new model to the task of reading comprehension in Vietnamese. Specifically, we use BLANC (BLock AttentioN for Context prediction) on pre-trained baseline models to solve the Machine reading comprehension (MRC) task on Vietnamese. We have achieved good results when using BLANC on the baseline model. Specifically, with the MRC task at the VLSP share-task 2021, we scored 76.877% of F1-score on the private test and ranked 2nd in the total. This shows that BLANC works very well in MRC tasks and further enhances the Vietnamese MRC development.","PeriodicalId":416488,"journal":{"name":"VNU Journal of Science: Computer Science and Communication Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"VNU Journal of Science: Computer Science and Communication Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25073/2588-1086/vnucsce.316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
MRC is challenging the natural language processing fields; machines automatically have to answer questions based on specific passages for this task. In recent years, machine reading comprehension (MRC) has received much attention; many articles have been written about this task. However, most of those articles only develop models in two main languages, English and Chinese. In this article, we propose to apply a new model to the task of reading comprehension in Vietnamese. Specifically, we use BLANC (BLock AttentioN for Context prediction) on pre-trained baseline models to solve the Machine reading comprehension (MRC) task on Vietnamese. We have achieved good results when using BLANC on the baseline model. Specifically, with the MRC task at the VLSP share-task 2021, we scored 76.877% of F1-score on the private test and ranked 2nd in the total. This shows that BLANC works very well in MRC tasks and further enhances the Vietnamese MRC development.