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README.md

@@ -137,29 +137,64 @@ All fertility and CPT metrics include **bootstrap 95% confidence intervals** (n=
 ### Morph Edit Distance Heatmap
 ![Morph Edit Distance Heatmap](plots/morph_edit_distance_ar_heatmap_v2.png)
 
+## Comparison with Existing Tokenizers
+
+We compared our best tokenizer per vocabulary size against five existing Arabic and Darija tokenizers from HuggingFace:
+
+| Tokenizer | Source | V | Fertility ↓ | Disparity ↓ | EM (Ar) | EM (Az) |
+|-----------|--------|---|-------------|-------------|---------|---------|
+| **Ours: concat BPE 8K** | Darija-specific | 8K | **1.625** | **0.089** | **99.9%** | **99.6%** |
+| **Ours: concat BPE 16K** | Darija-specific | 16K | **1.443** | **0.084** | **99.9%** | **99.6%** |
+| **Ours: concat BPE 32K** | Darija-specific | 32K | **1.270** | **0.084** | -- | -- |
+| CaMeLBERT-MSA | MSA | 30K | 2.289 | 0.427 | 29.9% | 38.9% |
+| Asafaya-BERT | MSA | 32K | 2.143 | 0.358 | 19.9% | 15.2% |
+| Aranizer-SP-86k | MSA | 86K | 1.918 | 0.368 | 99.8% | 99.6% |
+| DarijaBERT-ar | Darija | 80K | 1.761 | 0.410 | 13.7% | 8.0% |
+| DarijaBERT-az | Darija | 110K | 1.575 | 0.055 | 14.8% | 8.0% |
+
+Key results:
+- Our **8K** tokenizer (1.625) outperforms all MSA tokenizers (2.143–2.289) by **29–45%** in fertility, despite being 4–11× smaller in vocabulary
+- Our **32K** tokenizer (1.270) outperforms **all** external tokenizers including DarijaBERT-az (1.575) by **19%**
+- All external tokenizers (except DarijaBERT-az) exhibit cross-script disparity > 0.35; our tokenizers maintain ≤ 0.089
+- Our tokenizers achieve >99% exact match; most external BERT-based tokenizers fail to reconstruct Darija text (<40%)
+- `eval_and_compare.py` — Reproducible comparison script
+- `external_comparison.csv` / `.json` — Full comparison results
+
+![External Comparison](plots/external_comparison.png)
+
 ## Repository Structure
 
 ```
 daa-tokenizers/
 ├── README.md                          # This file
 ├── script.py                          # Benchmark script (reproducible)
+├── eval_and_compare.py               # External tokenizer comparison script
 ├── tokenizer_results.csv              # Full metrics table
 ├── tokenizer_results.json             # Full metrics (JSON)
 ├── bootstrap_ci.csv                   # Bootstrap 95% CIs
+├── external_comparison.csv           # Comparison with external tokenizers
+├── external_comparison.json          # Comparison with external tokenizers (JSON)
 ├── benchmark_report.md                # Detailed report
 ├── morphology/
 │   └── farasa_segmentations.json      # Cached Farasa morph segmentations (~100MB)
-├── tokenizers/                        # Raw tokenizer JSON files (36 files)
-├── transformers_tokenizers/           # 28 dirs for transformers library
+├── tokenizers/                        # Raw tokenizer JSON files (40 files)
+├── transformers_tokenizers/           # 32 dirs for transformers library
 │   ├── shared_bpe_8000/
 │   ├── shared_bpe_16000/
 │   ├── ...
 │   ├── concat_bpe_8000_tokenizer_ar/
 │   ├── concat_bpe_8000_tokenizer_az/
-│   └── ...
-└── plots/                             # 24 visualization PNGs
+│   ├── ...
+│   ├── concat_bpe_32000_tokenizer_ar/  # Newly trained
+│   ├── concat_bpe_32000_tokenizer_az/  # Newly trained
+│   ├── concat_unigram_32000_tokenizer_ar/
+│   ├── concat_unigram_32000_tokenizer_az/
+│   ├── concat_wordpiece_32000_tokenizer_ar/
+│   └── concat_wordpiece_32000_tokenizer_az/
+└── plots/                             # 25 visualization PNGs
     ├── fertility_overall_comparison_v2.png
     ├── bootstrap_ci_forest.png
+    ├── external_comparison.png
     ├── morph_edit_distance_ar_heatmap_v2.png
     └── ...
 ```