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Update 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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- #### Pro 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:
@@ -198,14 +198,6 @@ The toolkit generates five benchmarks of increasing complexity, based on the Doc
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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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- ```
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- Easiest → Mono-Seq → Mono-Rand → Poly-Seq → Poly-Int → Poly-Rand → Hardest
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- ```
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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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@@ -461,6 +453,7 @@ for Document Packet Recognition and Splitting},
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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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