Document identification and checking method and device based on large model

By using large-scale model technology, combining visual and linguistic large-scale models, end-to-end document recognition and verification can be achieved, solving the problems of low recognition accuracy and time-consuming and labor-intensive processes in existing technologies. This improves the efficiency and accuracy of document processing and adapts to the needs of different business scenarios.

CN120975100AActive Publication Date: 2025-11-18TUGUAN (TIANJIN) DIGITAL TECH CO LTD
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Patent Information

Application Number
CN202511503346.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-10-21
Publication Date
2025-11-18
Estimated Expiration
2045-10-21

AI Technical Summary

Technical Problem

Existing technologies in document processing suffer from low recognition accuracy, are time-consuming and labor-intensive, and lack flexibility and versatility, making it difficult to meet the needs for efficient and accurate document processing.

Method used

Employing large-scale model technology, combining visual and linguistic large-scale models, we achieve end-to-end conversion from unstructured documents to structured data, construct a dynamic dual-engine retrieval mechanism, and combine general and business-specific verification rules with RAG retrieval enhancement generation technology for verification.

Benefits of technology

It improves the accuracy of document recognition and the flexibility and adaptability of verification, reduces manual intervention, increases work efficiency, ensures that verification results comply with the latest industry standards and regulations, and reduces legal risks.

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Abstract

The invention provides a document recognition and checking method and device based on a large model. The method comprises the steps that a document to be recognized is obtained, the document is converted into a picture format, the obtained document picture is input into a pre-trained visual large model, and recognized information is output. Inputting information recognized by the visual large model into a language large model, writing field information needing to be extracted through a cue word project, guiding the language large model to perform keyword extraction on the input information, and outputting the field information needing to be extracted in a structured mode; configuring a checking rule, including constructing a checking script and a checking rule knowledge base; inputting the output data into a large checking model, constructing a dynamic double-engine retrieval mechanism by the large checking model in combination with an RAG retrieval enhancement generation technology, and checking the input information; and generating a checking result, and performing visual display. According to the invention, the accuracy and robustness of recognition of various documents can be improved.
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