Why LLMs Suck at OCR
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LLMs struggle with OCR due to their probabilistic nature and their tendency to prioritize semantic understanding over precise character recognition. They face challenges with complex layouts, unusual fonts, and tables, leading to errors and hallucinations. These models often produce plausible but incorrect outputs, making them unreliable for business-critical applications like financial and medical data extraction. Traditional OCR systems and new approaches combining computer vision with vision transformers show promise in addressing these issues.
Table of contents
I. How Do LLMs “See” and Process Images?II. Where Do Hallucinations Come From?III. Real-World Failures and Hidden RisksSort: