Why document parsing is still hard A scanned page looks simple to a person, but it is a messy input for software. Text can appear in columns, tables can span pages, formulas can mix with prose, and charts can carry information that ordinary OCR often flattens into garbled text. Traditional OCR pipelines usually split the job into several steps: detect layout, find text lines, recognize characters, and then try to rebuild structure. That works reasonably well on clean documents, but it struggles when the page contains mixed formats or when the reading order is not obvious. PaddleOCR-VL is a recent attempt to make that pipeline more practical. The official tutorial describes it as a compact document parsing model built around a NaViT-style dynamic-resolution visual encoder and the ERNIE-4.5-0.3B language model, with a two-stage flow: layout analysis first, then VLM-based recognition.…