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@@ -14,7 +14,7 @@ license: apache-2.0
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- <h1>DocExplainer: Visual Document QA with Bounding Box Localization</h1>
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  [![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
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  <!-- [![arXiv](https://img.shields.io/badge/arXiv-2501.03403-b31b1b.svg)]() -->
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  ## Model description
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- DocExplainer is a an approach to Visual Document Question Answering (Document VQA) with bounding box localization.
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  Unlike standard VLMs that only provide text-based answers, DocExplainer adds **visual evidence through bounding boxes**, making model predictions more interpretable.
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  It is designed as a **plug-and-play module** to be combined with existing Vision-Language Models (VLMs), decoupling answer generation from spatial grounding.
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+ <h1>DocExplainer: Document VQA with Bounding Box Localization</h1>
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  [![License: CC BY 4.0](https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
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  <!-- [![arXiv](https://img.shields.io/badge/arXiv-2501.03403-b31b1b.svg)]() -->
 
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  ## Model description
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+ DocExplainer is a an approach to Document Visual Question Answering (Document VQA) with bounding box localization.
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  Unlike standard VLMs that only provide text-based answers, DocExplainer adds **visual evidence through bounding boxes**, making model predictions more interpretable.
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  It is designed as a **plug-and-play module** to be combined with existing Vision-Language Models (VLMs), decoupling answer generation from spatial grounding.
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