Update README.md

README.md

@@ -56,30 +56,17 @@ Each entry in `metadata.jsonl` follows this schema:
 
 We evaluated **UI-TapBench** across leading Large Multimodal Models (LMMs) to measure tap accuracy, spatial and precision for mobile UI interactions.
 
-### 🏆 Drizz Benchmark Result
-
-| Model | Accuracy | Precision | Recall | F1 Score |
-|---|---:|---:|---:|---:|---:|---:|
-|Drizz | 94.51 | 96.22 | 98.16 | 97.18 |
-
-This represents the benchmark achieved by the **Drizz evaluation framework** on UI-TapBench.
-
----
-
 ### 🔍 Competitor Comparison
 
-| Model | Accuracy | Precision | Recall | F1 Score | 
-|---|---:|---:|---:|---:|---:|---:|
-| gpt-5.1 | 21.72 | 23.35 | 75.61 | 35.68 | 
-| gpt-5.2 | 44.83 | 45.71 | 95.88 | 61.91 | 
+| Model | Accuracy | Precision | Recall | F1 Score |
+|---|---:|---:|---:|---:|
+| **Drizz (ours)** | **94.51** | **96.22** | **98.16** | **97.18** |
+| gpt-5.1 | 21.72 | 23.35 | 75.61 | 35.68 |
+| gpt-5.2 | 44.83 | 45.71 | 95.88 | 61.91 |
 | gemini-pro | 89.84 | 91.28 | 98.28 | 94.65 |
-| gemini-flash | 81.44 | 83.78 | 96.67 | 89.77 | 
-| qwen3.5-27b | 92.98 | 94.98 | 97.61 | 96.28 | 
-
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+| gemini-flash | 81.44 | 83.78 | 96.67 | 89.77 |
+| qwen3.5-27b | 92.98 | 94.98 | 97.61 | 96.28 |
 
 ### 💡 Key Takeaway
 
 The results show that while several models perform well on general UI grounding tasks, **Drizz** demonstrates the highest benchmark performance on **UI-TapBench**, achieving strong spatial precision and reliable tap execution even in dense mobile UI layouts.
-
-This highlights the importance of evaluating not just reasoning quality, but exact coordinate prediction accuracy for real-world mobile automation systems.