[Lerc]

I guess it depends on the use case, but if it surpasses the error rate that exists in the source document then it would be difficult to argue against.

Specific things like evidentiary use would want 100% but that's at a level where any document processing would be suspect.

What is the the typical range for error rate in PDF generation in various fields? Even robust technical documents have the occasional typo.

[llm_trw]

I'm not using generative models to fill in details not present in the original document. If there's a typo there then there will be a typo in the transcript. If you want to fix that then you can run another model on top of it.

[Lerc]

I realise that. The point is that a user is implicitly committing to the baseline error rate that exists in whatever means by which the document was created. If any additional loss was insignificant in proportion to that error rate then it would be unreasonable to reject it on that basis.

[yigitkonur35]

You're right. For my API that prepares PDFs for LLMs, fixing typos makes sense. But yeah, keeping original text is crucial for most OCR tasks.