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Exactly my experience. If you try to OCR hand-filled forms with a fixed structure, traditional OCR models are great. Vision-llms can improve a bit on character recognition, but at the cost of harder to detect failure modes.

But if you are trying to ingest diverse documents with headings, multi-column layouts, headers and footers, ad space in the middle of your text, etc, vision-llms are a giant step forward. But you need the context of the previous page to make good decisions about the current page, which is where things quickly get janky (or slow, if you choose the naive approach)

Vision-llms also seem to deal much better with variance in scripts. Cursive, random Japanese in the middle of the text, weird math symbols, handwriting from three centuries ago, all "just works" without you even having to remember that this can happen

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