Demystifying PDF Parsing 03: OCR-Free Small Model-Based Method

Overview, Principles and Insights

PDF files can be challenging to convert into other formats, often locking substantial information in a format that is inaccessible to AI applications. If we could transform PDF files or their corresponding images into structured or semi-structured formats that are machine-readable, it would significantly alleviate this problem. This can also significantly enhance the knowledge base of artificial intelligence applications.

This series of articles is dedicated to demystifying PDF Parsing. In the first article of this series, we introduced the main task of PDF parsing, categorized existing methods, and provided brief introductions to each. And in the second article of this series, we focused on the pipeline-based method.

This article is the third in the series, introducing another approach to PDF parsing: OCR-free small model-based method. We begin with an overview, then introduce the principles of various representative OCR-free small model-based PDF parsing solutions. Lastly, we share the insights and thoughts we’ve gained.

Please note that the “small model” referred to in this article is relatively small compared to large multimodal models, typically having fewer than 1.5 billion parameters.