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Research2026-06-25 · source-backed

OCR-reasoning scores fall apart under visual perturbations.

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Right as Mistral OCR 4 makes self-hosted document AI viable, arXiv 2606.26041 shows VLM OCR-reasoning that looks strong on clean images degrades meaningfully when you add noise, blur, or distortion. Clean-input accuracy is not deployment accuracy. If you're putting a VLM OCR pipeline into production over phone-camera scans and faxed PDFs, benchmark it on ugly inputs, because that's what your users will feed it.

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