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- ```markdown
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- # Financial Document Extraction & Robustness Dataset (FinDoc-Robust)
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-
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- ## Dataset Description
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- FinDoc-Robust is a multimodal, benchmark-grade dataset designed for **Document Layout Analysis (DLA)**, **Visual Information Extraction (VIE)**, and evaluating model robustness against real-world degradation.
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-
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- The dataset contains financial reports across **5 distinct document categories** (e.g., cash flow statements, balance sheets, trial balances, shareholders' equity, corporate income statements). For every document, it provides perfect digital vectors, tabular ground truths, pixel-level bounding boxes, and **5 structurally degraded ("dirty") variants** simulating camera captures, scans, and physical artifacts.
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-
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- ### Key Applications
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- * **Robust Document AI:** Training models to resist geometric distortions, noise, and blur.
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- * **Table Reconstruction:** Benchmarking end-to-end Image-to-Excel/HTML/Markdown pipelines.
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- * **Multimodal Alignment:** Fine-tuning models like LayoutLMv3, Donut, or proprietary Vision-LLMs on complex financial structures.
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-
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- ---
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-
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- ## Dataset Structure
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-
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- The repository is organized hierarchically by document type and numerical index. Each sample folder contains a complete sub-set of modalities:
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-
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- ```text
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- dataset_root/
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- ├── new_type_cash_flow_statement/
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- ├── new_type_shareholders_equity/
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- ├── new_type_trial_balance/
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- ├── pro_doc_corporate_income_statement/
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- └── pro_doc_full_balance_sheet/
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- ├── 001/
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- │ ├── 001.pdf # Original clean vector PDF
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- │ ├── 001.png # Rendered high-res image (clean)
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- │ ├── 001.xlsx # Target ground-truth table structure
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- │ ├── 001.json # Word/Phrase Bounding Boxes (Pixel space)
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- │ ├── 001_pdf.json # Word/Phrase Bounding Boxes (DTP Point space)
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- │ ├── 001_dirty_1.png # Degraded scan/photo simulation variant 1
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- │ ├── 001_dirty_1.json # Adjusted Bounding Boxes for variant 1
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- │ ...
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- │ ├── 001_dirty_5.png # Degraded variant 5
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- │ └── 001_dirty_5.json # Adjusted Bounding Boxes for variant 5
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- └── 1001/ # Scale-tested deep indices (up to 4 digits)
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- ...
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-
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- ```
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  ```
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