Papers › A Graphical Approach to Document Layout Analysis
A Graphical Approach to Document Layout Analysis
Jilin Wang, Michael Krumdick, Baojia Tong, Hamima Halim, Maxim Sokolov, Vadym Barda, Delphine Vendryes, Chris Tanner
Document layout analysis (DLA) is the task of detecting the distinct, semantic content within a document and correctly classifying these items into an appropriate category (e.g., text, title, figure). DLA pipelines enable users to convert documents into structured machine-readable formats that can then be used for many useful downstream tasks. Most existing state-of-the-art (SOTA) DLA models represent documents as images, discarding the rich metadata available in electronically generated PDFs. Directly leveraging this metadata, we represent each PDF page as a structured graph and frame the DLA problem as a graph segmentation and classification problem. We introduce the Graph-based Layout Analysis Model (GLAM), a lightweight graph neural network competitive with SOTA models on two challenging DLA datasets - while being an order of magnitude smaller than existing models. In particular, the 4-million parameter GLAM model outperforms the leading 140M+ parameter computer vision-based model on 5 of the 11 classes on the DocLayNet dataset. A simple ensemble of these two models achieves a new state-of-the-art on DocLayNet, increasing mAP from 76.8 to 80.8. Overall, GLAM is over 5 times more efficient than SOTA models, making GLAM a favorable engineering choice for DLA tasks.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Document Layout Analysis | PubLayNet val | GLAM | Figure | 0.206 | #14 of 15 | Archive leaderboard | report |
| Document Layout Analysis | PubLayNet val | GLAM | List | 0.862 | #14 of 15 | Archive leaderboard | report |
| Document Layout Analysis | PubLayNet val | GLAM | Overall | 0.722 | #14 of 15 | Archive leaderboard | report |
| Document Layout Analysis | PubLayNet val | GLAM | Table | 0.868 | #14 of 15 | Archive leaderboard | report |
| Document Layout Analysis | PubLayNet val | GLAM | Text | 0.878 | #14 of 15 | Archive leaderboard | report |
| Document Layout Analysis | PubLayNet val | GLAM | Title | 0.800 | #14 of 15 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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