Unverified50% confidenceFactExact time
The OCR route commonly uses tools such as Tesseract and PaddleOCR to first obtain plain text and then hand it to a language model to determine the fields; end-to-end vision models (such as Donut and Qwen-VL) skip explicit OCR and predict structured output directly from the image.
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50%
Confidence
Long-term
Relevance
10/13/2026
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UnverifiedOCR tools designed for LLMs increasingly tend to output Markdown or structured-markup text so that models can correctly parse hierarchical relationships77% similarUnverifiedThe typical pipeline of traditional OCR technology includes: image preprocessing, layout analysis, character segmentation, feature extraction, character classification, and language model post-processing.74% similarUnverifiedOCR技术通过卷积神经网络识别图像中的文字，主流工具包括开源的Tesseract和商业化的百度OCR、腾讯云OCR73% similarUnverified传统OCR工具如Tesseract依赖字符模板匹配，对排版格式敏感且难以处理复杂布局73% similarUnverified多模态模型的文本识别并非通过独立OCR子模块实现，而是作为视觉-语言对齐训练的产物内嵌在模型权重中，图片文字与普通文本共享同一套语义处理管线72% similar
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