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Research questionHow can OCR diagnose and correct case-level errors while preserving rendering-equivalent outputs?Aggregate OCR scores can hide localized omissions and hallucinations in formulas, structured text, and unusual document formats. Different textual encodings can also render the same visible content, making valid alternatives difficult to distinguish from genuine errors.
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Computer Vision
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Image & Video Processing
Natural Language Processing
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Latest papersRecent research connected to this question, newest first.OCR-EDR: Rendering-Aware Diagnosis and Repair for Closed-Loop OCR ImprovementThe source addresses a rendering-aware OCR workflow that receives a source image, an editable OCR prediction, and its rendered image. It evaluates consistency, identifies and localizes genuine errors, and applies executable edits with possible iterative re-rendering. Evidence comes from OCRErrBench, DOCRcaseBench, and identified error subsets in UniMER-Test, with reported results for text and formula OCR; the evidence does not establish broader deployment capabilities beyond these settings.research paper · Sep 3, 2026
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