Hitomi Yanaka, Yuta Nakamura, Yuki Chida, Tomoya Kurosawa
{"title":"医学视觉文本蕴涵对视觉和语言模型的数值理解","authors":"Hitomi Yanaka, Yuta Nakamura, Yuki Chida, Tomoya Kurosawa","doi":"10.18653/v1/2023.clinicalnlp-1.2","DOIUrl":null,"url":null,"abstract":"Assessing the capacity of numerical understanding of vision-and-language models over images and texts is crucial for real vision-and-language applications, such as systems for automated medical image analysis.We provide a visual reasoning dataset focusing on numerical understanding in the medical domain.The experiments using our dataset show that current vision-and-language models fail to perform numerical inference in the medical domain.However, the data augmentation with only a small amount of our dataset improves the model performance, while maintaining the performance in the general domain.","PeriodicalId":216954,"journal":{"name":"Clinical Natural Language Processing Workshop","volume":"28 24","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Medical Visual Textual Entailment for Numerical Understanding of Vision-and-Language Models\",\"authors\":\"Hitomi Yanaka, Yuta Nakamura, Yuki Chida, Tomoya Kurosawa\",\"doi\":\"10.18653/v1/2023.clinicalnlp-1.2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Assessing the capacity of numerical understanding of vision-and-language models over images and texts is crucial for real vision-and-language applications, such as systems for automated medical image analysis.We provide a visual reasoning dataset focusing on numerical understanding in the medical domain.The experiments using our dataset show that current vision-and-language models fail to perform numerical inference in the medical domain.However, the data augmentation with only a small amount of our dataset improves the model performance, while maintaining the performance in the general domain.\",\"PeriodicalId\":216954,\"journal\":{\"name\":\"Clinical Natural Language Processing Workshop\",\"volume\":\"28 24\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Natural Language Processing Workshop\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18653/v1/2023.clinicalnlp-1.2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Natural Language Processing Workshop","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18653/v1/2023.clinicalnlp-1.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Medical Visual Textual Entailment for Numerical Understanding of Vision-and-Language Models
Assessing the capacity of numerical understanding of vision-and-language models over images and texts is crucial for real vision-and-language applications, such as systems for automated medical image analysis.We provide a visual reasoning dataset focusing on numerical understanding in the medical domain.The experiments using our dataset show that current vision-and-language models fail to perform numerical inference in the medical domain.However, the data augmentation with only a small amount of our dataset improves the model performance, while maintaining the performance in the general domain.