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--- |
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task_categories: |
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- visual-question-answering |
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language: |
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- en |
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size_categories: |
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- 1K<n<10K |
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--- |
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# Dataset Card for BloomVQA |
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### Dataset Description |
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<!-- Provide a longer summary of what this dataset is. --> |
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BloomVQA is a dataset based on picture stories designed for educating young children. |
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It aims to facilitate comprehensive evaluation and characterization of vision-language models on comprehension tasks. |
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The dataset contains tasks reflecting 6 different levels of comprehension and underlying cognitive processes, |
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as laid out in Bloom's Taxonomy, a classic framework widely adopted in education research. |
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This underlying hierarchical taxonomy enables graded model evaluation, automatic data augmentation and novel metrics characterizing model consistency. |
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The core dataset contains 1200 multiple-choice samples collected via Amazon Mechanical Turk based on 20 picture stories downloaded from Creative Commons resources [Book Dash](https://bookdash.org/) and [Storyweaver](https://storyweaver.org.in/en/). |
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<!-- Provide the basic links for the dataset. --> |
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- **Paper:** [BloomVQA: Assessing Hierarchical Multi-modal Comprehension](https://arxiv.org/abs/2312.12716) |
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## Dataset Structure |
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<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> |
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Each multiple-choice sample contains 1 question and 4 free-form answers including 1 correct answer and 3 incorrect answers. Each sample is labeled with the title of picture story and the level of comprehension as defined in Bloom's Taxonomy. |
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