Datasets:

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AdaptVis

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all_datasets

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This PR significantly enhances the dataset card for "Why Is Spatial Reasoning Hard for VLMs? An Attention Mechanism Perspective on Focus Areas" by providing comprehensive information for better discoverability and usability.

Key changes include:

• Metadata: Added task_categories: ['image-text-to-text'], language: ['en'], and relevant tags (vlm, spatial-reasoning, attention). The dataset_info and configs have been moved from top-level YAML to a dedicated "Dataset Structure" section in the Markdown content for clearer separation of general metadata and dataset schema.
• Paper & Code Links: Included direct links to the paper (https://huggingface.co/papers/2503.01773) and the GitHub repository (https://github.com/shiqichen17/AdaptVis).
• Abstract: The full paper abstract has been added to provide immediate context for the dataset.
• Visual: Embedded the main image from the GitHub repository.
• Sample Usage: Detailed instructions from the GitHub README are provided, including environment setup, data downloading, and running experiments with code snippets and an argument table. A load_dataset example using the datasets library is also included for easy integration with Hugging Face workflows.
• Dataset Structure: The existing dataset_info and configs have been moved to a new "Dataset Structure" section in Markdown, clarifying the schema of the different dataset configurations.
• Citation: The BibTeX citation from the paper has been added.

These updates make the dataset card much more informative and accessible for researchers on the Hugging Face Hub.