READoc: A Unified Benchmark for Realistic Document Structured Extraction

Document Structured Extraction (DSE) aims to extract structured content from raw documents.Despite the emergence of numerous DSE systems, their unified evaluation remains inadequate, significantly hindering the field's advancement.This problem is largely attributed to existing benchmark paradigms, which exhibit fragmented and localized characteristics.To offer a thorough evaluation of DSE systems, we introduce a novel benchmark named READOC, which defines DSE as a realistic task of converting unstructured PDFs into semantically rich Markdown.The READOC dataset is derived from 3,576 diverse and real-world documents from arXiv, GitHub, and Zenodo.In addition, we develop a DSE Evaluation S 3 uite comprising Standardization, Segmentation and Scoring modules, to conduct a unified evaluation of state-of-theart DSE approaches.By evaluating a range of pipeline tools, expert visual models, and general Vision-Language Models, we identify the gap between current work and the unified, realistic DSE objective for the first time.We aspire that READOC will catalyze future research in DSE, fostering more comprehensive and practical solutions.

Authors

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.findings-acl.1128
Citations
1
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
2.48

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article

READoc: A Unified Benchmark for Realistic Document Structured Extraction

Zichao Li, Zheng Jia, Bin Dong, Xuanang Chen et al.
1 citations
Natural Language Processing Techniques
2.48
article

READoc: A Unified Benchmark for Realistic Document Structured Extraction

Zichao Li, Zheng Jia, Bin Dong, Xuanang Chen, Hongyu Lin, Yaojie Lu, Xianpei Han, Shanshan Jiang, Le Sun, Aizier Abulaiti
article en
1 citations

Abstract

Document Structured Extraction (DSE) aims to extract structured content from raw documents.Despite the emergence of numerous DSE systems, their unified evaluation remains inadequate, significantly hindering the field's advancement.This problem is largely attributed to existing benchmark paradigms, which exhibit fragmented and localized characteristics.To offer a thorough evaluation of DSE systems, we introduce a novel benchmark named READOC, which defines DSE as a realistic task of converting unstructured PDFs into semantically rich Markdown.The READOC dataset is derived from 3,576 diverse and real-world documents from arXiv, GitHub, and Zenodo.In addition, we develop a DSE Evaluation S 3 uite comprising Standardization, Segmentation and Scoring modules, to conduct a unified evaluation of state-of-theart DSE approaches.By evaluating a range of pipeline tools, expert visual models, and general Vision-Language Models, we identify the gap between current work and the unified, realistic DSE objective for the first time.We aspire that READOC will catalyze future research in DSE, fostering more comprehensive and practical solutions.

National Natural Science Foundation of China
Openalex Percentile: Top 9%
Natural Language Processing Techniques
2.48
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READoc: A Unified Benchmark for Realistic Document Structured Extraction — Zichao Li, Zheng Jia, et al. · (2025) | TGRS Research Map | TGRS