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Baidu releases MarathonDocBench for 100-300-page document parsing

AIBaidu releases MarathonDocBench, a benchmark for parsing 100–300-page Chinese and English documents, with about 18,000 pages and 205,000 annotated layout elements. Human-refined annotations cover bounding boxes, heading hierarchy, reading order, and cross-page text and table continuations.
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Baidu's MarathonDocBench evaluates the parsing of 100–300-page Chinese and English documents, including cross-page text, tables, and document structure. 🤖https://modelscope.ai/datasets/baidu/MarathonDocBench

📚 Hundred-page scale: 100 documents, approximately 18,000 pages, and 205,000 annotated layout elements.

🔗 Structure across pages: Human-refined annotations cover bounding boxes, heading hierarchy, reading order, and cross-page text and table continuations.

🧪 Document-level evaluation: Reuses MPDocBench-Parse's eight metrics to assess text, tables, formulas, reading order, figures, and heading structure. Overall is their mean.

📊 A demanding test: Listed general-purpose VLMs score below 34 Overall under the published whole-document protocol, which counts failed requests as empty predictions. Input and output limits also affect results.

📜 Apache-2.0 License.

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Original title: Baidu's MarathonDocBench evaluates the parsing of 100–300-page Chinese and English documents, including cross-page text, tables, and docu...