Datasets:
Size:
1M<n<10M
ArXiv:
Tags:
Document_Understanding
Document_Packet_Splitting
Document_Comprehension
Document_Classification
Document_Recognition
Document_Segmentation
DOI:
License:
Update README.md
Browse files
README.md
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@@ -109,7 +109,7 @@ cd doc_split
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pip install -r requirements.txt
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```
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####
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- **Check Disk Space**: Hugging Face datasets can be large. Check the "Files and versions" tab on the Hugging Face page to see the total size before downloading.
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- **Partial Clone**: If you only need specific files (e.g., code without large data files), use:
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- **Challenge**: Worst-case scenario with no structural assumptions
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- **Use Case**: Document management system failures or emergency recovery
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## Benchmark Complexity
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```
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Easiest → Mono-Seq → Mono-Rand → Poly-Seq → Poly-Int → Poly-Rand → Hardest
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```
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- **Mono-Seq**: Highest baseline performance (>93% packet accuracy)
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- **Poly-Rand**: Most challenging (20-30% degradation for weaker models)
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## Project Structure
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timestamp = {2024-02-04},
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note = {Accessed: 2026-02-04}
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}
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# License
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pip install -r requirements.txt
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```
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#### Tips
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- **Check Disk Space**: Hugging Face datasets can be large. Check the "Files and versions" tab on the Hugging Face page to see the total size before downloading.
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- **Partial Clone**: If you only need specific files (e.g., code without large data files), use:
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- **Challenge**: Worst-case scenario with no structural assumptions
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- **Use Case**: Document management system failures or emergency recovery
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## Project Structure
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timestamp = {2024-02-04},
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note = {Accessed: 2026-02-04}
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}
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```
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# License
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