OCRFlux-bench-cross

PDF documents are typically paginated, which often results in tables or paragraphs being split across consecutive pages. Accurately detecting and merging such cross-page structures is crucial to avoid generating incomplete or fragmented content.

The detection task can be formulated as follows: given the Markdowns of two consecutive pages—each structured as a list of Markdown elements (e.g., paragraphs and tables)—the goal is to identify the indexes of elements that should be merged across the pages.

OCRFlux-bench-cross is a benchmark of 1000 samples that can be used to measure the performance of OCR systems in the cross-page table/paragraph detection task.

Quick links:

• 🤗 Model
• 🛠️ Code

Data Mix

Table 1: Samples breakdown by language

Language	Samples
English	500
Chinese	500
Total	1000

Data Format

Each row in the dataset corresponds to two consecutive pages, their corresponding Markdown element lists and the indexes of elements that need to be merged. If no tables or paragraphs require merging, the indexes in the annotation data are left empty.

Features:

{
    'pdf_name_1': string,         # Name of the first PDF document
    'pdf_name_2': string,         # Name of the second PDF document
    'language': string,         # Language of the PDF document, zh or en
    'md_elem_list_1': list,       # List of the first page's Markdown elements
    'md_elem_list_2': list,       # List of the second page's Markdown elements
    'merging_idx_pairs': list,       # Pairs of Markdown element indexes in the first and second page which should be merged, be [] if no merge is needed
}

License

This dataset is licensed under Apache-2.0.