lmms-lab/FVQA

FactualVQA (FVQA)是一个用于搜索增强训练和评估的多模态视觉问答数据集。它侧重于需要外部信息（超出给定图像范围）的知识密集型问题。每个条目包括一个图像、一个问题和一个答案（可选伴随候选答案），使模型能够开发和优化按需搜索策略。数据集的构建细节在相关博客或论文中有提供。

FactualVQA (FVQA) is a multimodal Visual Question Answering dataset created for search-augmented training and evaluation. It emphasizes knowledge-intensive questions that require external information beyond the given image. Each entry includes an image, a question, and an answer (optionally accompanied by candidate answers), enabling models to develop and refine on-demand search strategies. Details of dataset construction are provided in the associated blog post or paper.