1 dépôt
Awesome GitHub RepositoriesDocument Content Refinement
Using language models to improve the accuracy and structural integrity of parsed document content.
Distinct from LLM-Based Analysis: Focuses on cleaning OCR and merging tables in documents rather than analyzing source code changes.
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Awesome Document Content Refinement GitHub Repositories
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- vikparuchuri/marker
VikParuchuri/marker
36,164Voir sur GitHubMarker is an LLM-powered document parser and OCR pipeline designed to convert PDFs and unstructured files into structured markdown, JSON, and HTML. It functions as a data preprocessor that transforms complex documents into machine-readable formats while preserving tables, equations, and layout structures. The system utilizes large language models to refine OCR accuracy, clean mathematical notation, and merge fragmented tables across multiple pages. It employs model-based layout analysis to predict block types and bounding boxes, ensuring a more precise conversion of document elements. Capabi
Uses large language models to merge fragmented tables across pages and clean up mathematical notation for higher precision.
Python
