Yes, but a lot of the improvement is coming from layout models and/or multimodal LLMs operating directly on the raster images, as opposed to via classical OCR. This gets better results because the PDF format does not necessarily impart reading order or semantic meaning; the only way to be confident you're reading it like a human would is to actually do so - to render it out.
Another thing is that most document parsing tasks are going to run into a significant volume of PDFs which are actually just a bunch of scans/images of paper, so you need to build this capability anyways.
TL;DR: PDFs are basically steganography
Hard no.
LLMs aren't going to magically do more than what your PDF rendering engine does, rastering it and OCR'ing doesn't change anything. I am amazed at how many people actually think it is a sane idea.
I think there is some kind of misunderstanding. Sure, if you get somehow structured, machine-generated PDFs parsing them might be feasible.
But what about the "scanned" document part? How do you handle that? Your PDF rendering engine probably just says: image at pos x,y with size height,width.
So as parent says you have to OCR/AI that photo anyway and it seems that's also a feasible approach for "real" pdfs.
Okay, this sounds like "because some part of the road is rough, why don't we just drive in the ditch along the road way all the way, we could drive a tank, that would solve it"?
My experience is that “text is actually images or paths” is closer to the 40% case than the 1% case.
So you could build an approach that works for the 60% case, is more complex to build, and produces inferior results, but then you still need to also build the ocr pipeline for the other 40%. And if you’re building the ocr pipeline anyway and it produces better results, why would you not use it 100%?