Update README.md

README.md

@@ -166,6 +166,50 @@ To reproduce the results in our paper, please refer to our repo for detailed ins
 
 For more details on the methodology and evaluation, please refer to our [paper](https://arxiv.org/abs/2508.05731) and [repository](https://github.com/InfiXAI/InfiGUI-G1).
 
+## Results
+
+Our InfiGUI-G1 models, trained with the AEPO framework, establish new state-of-the-art results among open-source models across a diverse and challenging set of GUI grounding benchmarks.
+
+### MMBench-GUI (L2) Results
+
+On the comprehensive MMBench-GUI benchmark, which evaluates performance across various platforms and instruction complexities, our InfiGUI-G1 models establish new state-of-the-art results for open-source models in their respective size categories.
+
+<div align="center">
+  <img src="https://raw.githubusercontent.com/InfiXAI/InfiGUI-G1/main/assets/results_mmbench-gui.png" width="90%" alt="MMBench-GUI Results">
+</div>
+
+### ScreenSpot-Pro Results
+
+On the challenging ScreenSpot-Pro benchmark, designed to test semantic understanding on high-resolution professional software, InfiGUI-G1 demonstrates significant improvements, particularly on icon-based grounding tasks. This highlights AEPO's effectiveness in enhancing semantic alignment by associating abstract visual symbols with their functions.
+
+<div align="center">
+  <img src="https://raw.githubusercontent.com/InfiXAI/InfiGUI-G1/main/assets/results_screenspot-pro.png" width="90%" alt="ScreenSpot-Pro Results">
+</div>
+
+### UI-Vision (Element Grounding) Results
+
+InfiGUI-G1 shows strong generalization capabilities on the UI-Vision benchmark, which is designed to test robustness across a wide variety of unseen desktop applications. Achieving high performance confirms that our AEPO framework fosters a robust understanding rather than overfitting to the training data.
+
+<div align="center">
+  <img src="https://raw.githubusercontent.com/InfiXAI/InfiGUI-G1/main/assets/results_ui-vision.png" width="90%" alt="UI-Vision Results">
+</div>
+
+### UI-I2E-Bench Results
+
+To further probe semantic reasoning, we evaluated on UI-I2E-Bench, a benchmark featuring a high proportion of implicit instructions that require reasoning beyond direct text matching. Our model's strong performance underscores AEPO's ability to handle complex, indirect commands.
+
+<div align="center">
+  <img src="https://raw.githubusercontent.com/InfiXAI/InfiGUI-G1/main/assets/results_i2e-bench.png" width="90%" alt="UI-I2E-Bench Results">
+</div>
+
+### ScreenSpot-V2 Results
+
+On the widely-used ScreenSpot-V2 benchmark, which provides comprehensive coverage across mobile, desktop, and web platforms, InfiGUI-G1 consistently outperforms strong baselines, demonstrating the broad applicability and data efficiency of our approach.
+
+<div align="center">
+  <img src="https://raw.githubusercontent.com/InfiXAI/InfiGUI-G1/main/assets/results_screenspot-v2.png" width="90%" alt="ScreenSpot-V2 Results">
+</div>
+
 ## Citation Information
 
 If you find this work useful, we would be grateful if you consider citing the following papers: