OCR Free

OCR-free document understanding aims to extract information from documents directly from images, bypassing the need for Optical Character Recognition (OCR). Current research focuses on developing large multimodal language models (MLLMs) that integrate visual and textual information, often employing transformer architectures and innovative training strategies like chain-of-thought prompting and frequency domain processing to improve efficiency and accuracy. These advancements offer significant potential for faster, more flexible, and language-agnostic document processing, impacting fields ranging from archival digitization to automated data entry.