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README.md

@@ -77,9 +77,10 @@ We conducted a comprehensive evaluation of **MOSS-VL-Instruct-0408** across four
 ### 🌟 Key Highlights
 
 *   **🚀 Leading Video Intelligence**: MOSS-VL achieves a score of **65.8** in Video Understanding, significantly outperforming Qwen3-VL (+2pts). It shows exceptional temporal consistency and action recognition capabilities across benchmarks like `VideoMME`, `MLVU`, `EgoSchema`, and `VSI-bench` (where it outperforms **Qwen3-VL-8B-Instruct** by **8.3 points**).
-*   **👁️ Outstanding Multimodal Perception**: With a score of **75.1**, MOSS-VL delivers excellent general image-text understanding, shining in fine-grained object recognition and spatial reasoning on benchmarks like `BLINK` and `MMBench`.
-*   **🧠 Robust Multimodal Reasoning**: Achieving **64.3**, MOSS-VL demonstrates solid logical inference, staying highly competitive with the latest Qwen series on challenging reasoning suites such as `CVBench` and `VisuLogic`.
+*   **👁️ Outstanding Multimodal Perception**: MOSS-VL delivers excellent general image-text understanding, shining in fine-grained object recognition and spatial reasoning on benchmarks like `BLINK` and `MMBench`.
+*   **🧠 Robust Multimodal Reasoning**: MOSS-VL demonstrates solid logical inference, staying highly competitive with the latest Qwen series on challenging reasoning suites such as `CVBench` and `VisuLogic`.
 *   **📄 Reliable Document Understanding**: While the model is primarily optimized for general perception and video, MOSS-VL still delivers **83.9** on OCR and document analysis, ensuring dependable extraction of text and structured information.
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 <p align="center">
     <img src="assets/benchmark_table.png" alt="MOSS-VL Benchmark Table" width="100%"/>
 </p>