LayoutLM
A pre-trained model for document understanding developed by Microsoft, integrating textual, layout, and image information. It is designed for structured information extraction from scanned documents and handles the interplay among these modalities.
Core Facts
Timeline (last 90 days)
Representative tools for the vision model approach include Unstructured.io, LlamaParse, Microsoft's LayoutLM series of models, and multimodal large models such as GPT-4V/Claude.
The LayoutLM series was introduced by Microsoft and incorporates three modalities—text, positional coordinates, and images—during the pre-training phase.
Multimodal pre-trained models represented by the LayoutLM series jointly model visual, textual, and positional information, advancing the capability frontier in the field of document understanding
Docling relies on layout detection models (the LayoutLM series) and table recognition models, which need to be loaded into memory on first run.
Mainstream layout-aware PDF extraction solutions are divided into rule-based tools (such as pdfplumber and PDFMiner) and vision model-based solutions (such as Microsoft LayoutLM, Amazon Textract, and Adobe PDF Extract API).
Microsoft's LayoutLM series of models can jointly understand text semantics and spatial layout, and are used for intelligent document processing.
The LayoutLM series of models integrates text, positional, and visual information into the Transformer architecture.
Microsoft's LayoutLM and Google's Document AI understand document layouts by fusing visual and language models.
All Facts (9)
Microsoft's LayoutLM and Google's Document AI understand document layouts by fusing visual and language models.
65%UnverifiedLayoutLM and Donut are representative specialized document understanding models.
60%UnverifiedRepresentative tools for the vision model approach include Unstructured.io, LlamaParse, Microsoft's LayoutLM series of models, and multimodal large models such as GPT-4V/Claude.
50%UnverifiedThe LayoutLM series was introduced by Microsoft and incorporates three modalities—text, positional coordinates, and images—during the pre-training phase.
50%UnverifiedMultimodal pre-trained models represented by the LayoutLM series jointly model visual, textual, and positional information, advancing the capability frontier in the field of document understanding
50%UnverifiedDocling relies on layout detection models (the LayoutLM series) and table recognition models, which need to be loaded into memory on first run.
50%UnverifiedMainstream layout-aware PDF extraction solutions are divided into rule-based tools (such as pdfplumber and PDFMiner) and vision model-based solutions (such as Microsoft LayoutLM, Amazon Textract, and Adobe PDF Extract API).
50%UnverifiedMicrosoft's LayoutLM series of models can jointly understand text semantics and spatial layout, and are used for intelligent document processing.
50%UnverifiedThe LayoutLM series of models integrates text, positional, and visual information into the Transformer architecture.
50%