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Traditional OCR neural networks like tesseract crucially they have strong measures of their accuracy levels, including when they employ dictionaries or the like
by tensor 2y ago
Traditional OCR neural networks like tesseract crucially they have strong measures of their accuracy levels, including when they employ dictionaries or the like to help with accuracy. LLMs, on the other hand, give you zero guarantees, and have some pretty insane edge cases.
With a traditional OCR architecture maybe you'll get a symbol or two wrong, but an LLM can give you entirely new words or numbers not in the document, or even omit sections of the document. I'd never use an LLM for OCR like this.
- mlyle 2y agoIf you use LLM stupidly, sure. You can get from the LLM pseudo-probabilities of next symbol and use e.g Bayes rule to combine the information of how well it matches the page. You can also report the total uncertainty at the end. Done properly, this should strictly improve the results.