allenai/olmOCR-bench
olmOCR-bench olmOCR-bench is a dataset of 1,403 PDF files, plus 7,010 unit test cases that capture properties of the output that a good OCR system should have. This benchmark evaluates the ability of OCR systems to accurately convert PDF documents to markdown format while preserving critical textual and structural information. Quick links: 📃 Paper 🛠️ Code 🎮 Demo Table 1. Distribution of Test Classes by Document Source Document Source Text Present Text… See the full description on the dataset page: https://huggingface.co/datasets/allenai/olmOCR-bench.
olmOCR-bench
olmOCR-bench is a dataset of 1,403 PDF files, plus 7,010 unit test cases that capture properties of the output that a good OCR system should have. This benchmark evaluates the ability of OCR systems to accurately convert PDF documents to markdown format while preserving critical textual and structural information.
Quick links:
Table 1. Distribution of Test Classes by Document Source
Table 2. Document source category breakdown
Evaluation Criteria
- Text Presence: Checks if a short text segment (1–3 sentences) is correctly identified in the OCR output. Supports fuzzy matching and positional constraints (e.g., must appear in the first/last N characters). Case-sensitive by default.
- Text Absence: Ensures specified text (e.g., headers, footers, page numbers) is excluded. Supports fuzzy matching and positional constraints. Not case-sensitive.
- Natural Reading Order: Verifies the relative order of two text spans (e.g., headline before paragraph). Soft matching enabled; case-sensitive by default.
- Table Accuracy: Confirms that specific cell values exist in tables with correct neighboring relationships (e.g., value above/below another). Supports Markdown and HTML, though complex structures require HTML.
- Math Formula Accuracy: Detects the presence of a target equation by matching symbol layout (e.g., $\int$ to the left of $x$). Based on rendered bounding boxes and relative positioning.
📊 Benchmark Results by Document Source
License
This dataset is licensed under ODC-BY-1.0. It is intended for research and educational use in accordance with AI2's Responsible Use Guidelines.
