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RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes

机译:复仇之乐:用于烹饪食谱的多式联理理解的挑战数据集

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Understanding and reasoning about cooking recipes is a fruitful research direction towards enabling machines to interpret procedural text. In this work, we introduce RecipeQA. a dataset for multimodal comprehension of cooking recipes. It comprises of approximately 20K instructional recipes with multiple modalities such as titles, descriptions and aligned set of images. With over 36K automatically generated question-answer pairs, we design a set of comprehension and reasoning tasks that require joint understanding of images and text, capturing the temporal flow of events and making sense of procedural knowledge. Our preliminary results indicate that RecipeQA will serve as a challenging test bed and an ideal benchmark for evaluating machine comprehension systems.
机译:关于烹饪食谱的理解和推理是朝向使机器解释程序文本的富有成果的研究方向。在这项工作中,我们介绍了复仇了。用于烹饪食谱的多式化理解的数据集。它包括大约20k的教学配方,其中具有多种模式,例如标题,描述和对准的图像集。通过超过36K自动生成的问题答案对,我们设计了一套理解和推理任务,需要共同了解图像和文本,捕获事件的时间流动并掌握程序知识。我们的初步结果表明,复仇会将作为挑战性试验台和用于评估机器理解系统的理想基准。

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