Since these are statistical classification problems, it seems like it would be worth trying some old-school machine learning (not an LLM, just an NN) to see how it compares with these manual heuristics.
PDF to Text, a challenging problem
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Re: PDF to Text, a challenging problem
#12Weird that there's no mention of LLMs in this article even though the article is very recent. LLMs haven't solved every OCR/document data extraction problem, but they've dramatically improved the situation.
Author here: LLMs are definitely the new gold standard for smaller bodies of shorter documents.
The article is in the context of an internet search engine, the corpus to be converted is of order 1 TB. Running that amount of data through an LLM would be extremely expensive, given the relatively marginal improvement in outcome.
Re: PDF to Text, a challenging problem
#13One thing I wish someone would write is something like the browser's developer tools ("inspect elements") for PDF — it would be great to be able to "view source" a PDF's content streams (the BT … ET operators that enclose text, each Tj operator for setting down text in the currently chosen font, etc), to see how every “pixel” of the PDF is being specified/generated. I know this goes against the current trend / state-…
Try with cpdf (disclaimer, wrote it):
cpdf -output-json -output-json-parse-content-streams in.pdf -o out.json
cpdf -j out.json -o out.pdf
Re: PDF to Text, a challenging problem
#14So many of these problems have been solved by mozilla pdf.js together with its viewer implementation: https://mozilla.github.io/pdf.js/ .
I don't think so, pdf.js is able to render a pdf content.
Which is different from extracting "text". Text in PDF can be encoded in many ways, in an actual image, in shapes (think, segments, quadratic bezier curves...), or in an XML format (really easy to process).
PDF viewers are able to render text, like a printer would work, processing command to show pixels on the screen at the end.
But often, paragraph, text layout, columns, tables are lost in the process. Even though, you see them, so close yet so far. That is why AI is quite strong at this task.
Re: PDF to Text, a challenging problem
#15Cloudflare’s ai.toMarkdown() function available in Workers AI can handle PDFs pretty easily. Judging from speed alone, it seems they’re parsing the actual content rather than shoving into OCR/LLM.
Shameless plug: I use this under the hood when you prefix any PDF URL with https://pure.md/ to convert to raw text.
Re: PDF to Text, a challenging problem
#16Since these are statistical classification problems, it seems like it would be worth trying some old-school machine learning (not an LLM, just an NN) to see how it compares with these manual heuristics.
I imagine that would work pretty well given an adequate and representative body of annotated sample data. Though that is also not easy to come by.
Re: PDF to Text, a challenging problem
#17One thing I wish someone would write is something like the browser's developer tools ("inspect elements") for PDF — it would be great to be able to "view source" a PDF's content streams (the BT … ET operators that enclose text, each Tj operator for setting down text in the currently chosen font, etc), to see how every “pixel” of the PDF is being specified/generated. I know this goes against the current trend / state-…
Have a look at this notebook[0], not exactly what you're looking for but does provide a 'live' inspector of the various drawing operations contained in a PDF.
Re: PDF to Text, a challenging problem
#18Cloudflare’s ai.toMarkdown() function available in Workers AI can handle PDFs pretty easily. Judging from speed alone, it seems they’re parsing the actual content rather than shoving into OCR/LLM. Shameless plug: I use this under the hood when you prefix any PDF URL with https://pure.md/ to convert to raw text.
If you're looking for test cases, this is the first thing I tried and the result is very bad: https://pure.md/https://docs.house.gov/meetings/IF/IF00/2025...
Re: PDF to Text, a challenging problem
#19When accommodating the general case, solving PDF-to-text is approximately equivalent to solving JPEG-to-text.
The only PDF parsing scenario I would consider putting my name on is scraping AcroForm field values from standardized documents.
Re: PDF to Text, a challenging problem
#20Cloudflare’s ai.toMarkdown() function available in Workers AI can handle PDFs pretty easily. Judging from speed alone, it seems they’re parsing the actual content rather than shoving into OCR/LLM. Shameless plug: I use this under the hood when you prefix any PDF URL with https://pure.md/ to convert to raw text.
You’re aware that PDFs are containers that can hold various formats, which can be interlaced in different ways, such as on top, throughout, or in unexpected and unspecified ways that aren’t “parsable,” right?
I would wager that they’re using OCR/LLM in their pipeline.