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  ## Performance
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- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/66436107bfa436269e92b10a/53foSyYSG55GgP1yGCyvn.png)
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Document VQA performance of different models and prompting strategies on the BoundingDocs v2.0 dataset. <br>
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  Smol stands for SmolVLM-2.2B, Qwen stands for Qwen2-VL-7B, and D.E. stands for DocExplainerV0. <br>
 
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  ## Performance
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+ | Architecture | Prompting | ANLS | MeanIoU |
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+ |--------------------------------|------------|-------|---------|
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+ | Smol | Zero-shot | 0.527 | 0.011 |
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+ | | Anchors | 0.543 | 0.026 |
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+ | | CoT | 0.561 | 0.011 |
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+ | Qwen | Zero-shot | 0.691 | 0.048 |
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+ | | Anchors | 0.694 | 0.051 |
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+ | | CoT | <ins>0.720</ins> | 0.038 |
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+ | Claude Sonnet 4 | Zero-shot | **0.737** | 0.031 |
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+ | Smol + D.E. | Zero-shot | 0.572 | 0.175 |
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+ | Qwen + D.E. | Zero-shot | 0.689 | 0.188 |
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+ | Smol + Naive OCR | Zero-shot | 0.556 | <ins>0.405</ins> |
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+ | Qwen + Naive OCR | Zero-shot | 0.690 | **0.494** |
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  Document VQA performance of different models and prompting strategies on the BoundingDocs v2.0 dataset. <br>
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  Smol stands for SmolVLM-2.2B, Qwen stands for Qwen2-VL-7B, and D.E. stands for DocExplainerV0. <br>