Document Parsing Unveiled: Techniques, Challenges, and Prospects for
  Structured Information Extraction
Document parsing is essential for converting unstructured and semi-structured
documents-such as contracts, academic papers, and invoices-into structured,
machine-readable data. Document parsing extract reliable structured data from
unstructured inputs, providing huge convenience for numerous applications.
Especially with recent achievements in Large Language Models, document parsing
plays an indispensable role in both knowledge base construction and training
data generation. This survey presents a comprehensive review of the current
state of document parsing, covering key methodologies, from modular pipeline
systems to end-to-end models driven by large vision-language models. Core
components such as layout detection, content extraction (including text,
tables, and mathematical expressions), and multi-modal data integration are
examined in detail. Additionally, this paper discusses the challenges faced by
modular document parsing systems and vision-language models in handling complex
layouts, integrating multiple modules, and recognizing high-density text. It
emphasizes the importance of developing larger and more diverse datasets and
outlines future research directions.
67207abcd9e8b7a75988e5a5
Qintong Zhang
claimed_verified
2024-10-30T09:53:15.937Z
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/avatars/56675f2bdbfa2fb535495f15bf5eabd5.svg
Zhang Qintong
user
ZQTTTT
67207abcd9e8b7a75988e5a6
Victor Shea-Jay Huang
claimed_verified
2024-10-30T09:53:14.073Z
65b5d65b625ac670a79b52a8
https://cdn-avatars.huggingface.co/v1/production/uploads/65b5d65b625ac670a79b52a8/aBPXeSgh-_HQQWuPN89OK.jpeg
Victor Shea-Jay Huang
user
jeix
67207abcd9e8b7a75988e5a7
Bin Wang
claimed_verified
2024-10-30T09:53:10.077Z
63ae9ff5557befe297a76f90
https://cdn-avatars.huggingface.co/v1/production/uploads/1672388558183-noauth.jpeg
Bin Wang
user
wanderkid
67207abcd9e8b7a75988e5a8
Junyuan Zhang
claimed_verified
2024-12-04T09:46:54.080Z
65411de281a8731a1c28293d
/avatars/18607dcd65303e1f688fae8015f43314.svg
junyuan
user
Carkham
67207abcd9e8b7a75988e5a9
Zhengren Wang
claimed_verified
2025-05-21T09:10:34.502Z
66431358af62c6c266b921ad
https://cdn-avatars.huggingface.co/v1/production/uploads/66431358af62c6c266b921ad/36VacSxNJSPM9Ap_35HSZ.jpeg
Wang
user
zr-wang
67207abcd9e8b7a75988e5aa
Hao Liang
67207abcd9e8b7a75988e5ab
Shawn Wang
67207abcd9e8b7a75988e5ac
Matthieu Lin
67207abcd9e8b7a75988e5ad
Wentao Zhang
67207abcd9e8b7a75988e5ae
Conghui He
Document Parsing Unveiled: Techniques, Challenges, and Prospects for
  Structured Information Extraction
Document parsing is essential for converting unstructured and semi-structured
documents-such as contracts, academic papers, and invoices-into structured,
machine-readable data. Document parsing extract reliable structured data from
unstructured inputs, providing huge convenience for numerous applications.
Especially with recent achievements in Large Language Models, document parsing
plays an indispensable role in both knowledge base construction and training
data generation. This survey presents a comprehensive review of the current
state of document parsing, covering key methodologies, from modular pipeline
systems to end-to-end models driven by large vision-language models. Core
components such as layout detection, content extraction (including text,
tables, and mathematical expressions), and multi-modal data integration are
examined in detail. Additionally, this paper discusses the challenges faced by
modular document parsing systems and vision-language models in handling complex
layouts, integrating multiple modules, and recognizing high-density text. It
emphasizes the importance of developing larger and more diverse datasets and
outlines future research directions.
The survey reviews document parsing methodologies, including modular pipeline systems and end-to-end models, focusing on layout detection, content extraction, and multi-modal data integration, while highlighting challenges and future research directions.
layout detection content extraction text tables mathematical expressions multi-modal data integration large vision-language models