Update README.md

README.md

@@ -238,24 +238,10 @@ The evaluation script currently includes:
 
 ---
 
-## 📊 ADG Scoring Intuition
-
-ADG is built around two complementary signals derived from multiple sampled answers:
-
-- **Dispersion magnitude**  
-  Measures how widely the sampled answers spread in representation space.
-
-- **Shape anisotropy**  
-  Measures whether the spread is multi-directional rather than dominated by a single direction.
-
-The final ADG score combines these two parts, and the selected subset is obtained through semantic bin-wise ranking. This design helps avoid collapsing selection into only a few dense instruction regions.
-
----
-
 ## 📖 Citation
 
 If you use this repository, please cite the paper.
-```json
+```bibtex
 @article{li2026instruction,
   title={Instruction Data Selection via Answer Divergence},
   author={Li, Bo and Wang, Mingda and Zhang, Shikun and Ye, Wei},