Update README.md

README.md

@@ -14,9 +14,7 @@ metrics:
 - f1
 ---
 
-# SEED — Simple & Efficient Expert Detector
-
-**SEED** (Simple & Efficient Expert Detector) is a lightweight vision transformer model for document forgery detection. It localizes tampered regions in document images and classifies images as real or forged.
+# SEED: Simple ViT and Evolving Harness for Explainable Text Forgery Detection
 
 ## Architecture
 
@@ -43,39 +41,6 @@ model.eval()
 #   - image_logits: image-level real vs forged classification
 ```
 
-## Performance
-
-Evaluated on 1,000 samples per dataset at 512×512:
-
-### Detection (image-level F1)
-| Dataset | F1 | Accuracy | Precision | Recall |
-|---------|-----|----------|-----------|--------|
-| T-SROIE | 0.88 | 0.88 | 0.90 | 0.86 |
-| Tampered-IC13 | 0.91 | 0.95 | 0.98 | 0.86 |
-| RealTextManipulation | 0.36 | 0.63 | 0.49 | 0.28 |
-| OSTF | 0.57 | 0.92 | 0.56 | 0.58 |
-
-### Localization (pixel-level F1)
-| Dataset | F1 |
-|---------|-----|
-| T-SROIE | 0.39 |
-| Tampered-IC13 | 0.26 |
-| RealTextManipulation | 0.04 |
-| OSTF | 0.05 |
-
-> **Note:** This is a lightweight LoRA rank-1 model trained for 5,000 steps. Higher localization performance can be achieved with larger LoRA ranks and longer training.
-
-## Citation
-
-```bibtex
-@software{seed2025,
-  title={SEED: Simple & Efficient Expert Detector for Document Forgery},
-  author={Mobile Perception Systems Lab, TU/e},
-  year={2025},
-  url={https://huggingface.co/Jason37437/SEED}
-}
-```
-
 ## License
 
 MIT License.