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README.md

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 <!-- ---
 license: MIT License
-task:
+tags:
+  - physics
   - understanding
-  - reasoning
   - generation
-domain:
-  - Multimodal
-language:
-  - en
-dataset_type: other
+  - reasoning
+  - multimodal
+language:  
+- en
 --- -->
 <p align="center" width="100%">
 <a target="_blank"><img src="figs/FysicsWorld-logo.png" alt="" style="width: 50%; min-width: 200px; display: block; margin: auto;"></a>
@@ -19,7 +18,14 @@ dataset_type: other
 <h1>FysicsWorld: A Unified Full-Modality Benchmark for Any-to-Any Understanding, Generation, and Reasoning</h1>
 
 
-<font size=3><div align='center' > [[🏠 Project Page](https://github.com/Fysics-AI/FysicsWorld)] [[📖 arXiv Paper](https://arxiv.org/pdf/2512.12756)] [[🤗 Dataset](https://huggingface.co/datasets/Fysics-AI/FysicsWorld)] [[👾 ModelScope](https://www.modelscope.cn/datasets/Fysics-AI/FysicsWorld)] [[🏆 Leaderboard](https://huggingface.co/spaces/Fysics-AI/FysicsWorld-Leaderboard)]  </div></font>
+<font size=3><div align='center' > 
+[[🏠 Project Page](https://github.com/Fysics-AI/FysicsWorld)] 
+[[📖 Paper](https://arxiv.org/pdf/2512.12756)] 
+[[🤗 Dataset](https://huggingface.co/datasets/Fysics-AI/FysicsWorld)] 
+[[👾 ModelScope](https://www.modelscope.cn/datasets/Fysics-AI/FysicsWorld)] 
+[[🏆 Leaderboard](https://huggingface.co/spaces/Fysics-AI/FysicsWorld-Leaderboard)] 
+[[🀄 中文版](README_zh.md)] 
+</div></font>
 
 
 </div>
@@ -38,7 +44,7 @@ We introduce ***FysicsWorld***, the **first** unified full-modality benchmark th
 
 * **Fusion-Dependent Cross-Modal Reasoning**. We propose a method for omni-modal data construction, which is named **C**ross-**M**odal **C**omplementarity **S**creening (**CMCS**) strategy, which ensures that our tasks maintain strong cross-modal coupling, preventing single-modality shortcuts and enforcing true synergistic perception of omni-modality.
 
-* **Speech-Driven Cross-Modal Interaction**. To support natural, multimodal communication and interaction, we develop a speech-grounded multimodal data construction pipeline that ensures both linguistic fluency and semantic fidelity in voice-based interactions, including 20+ authentic voices and tones.
+* **Speech-Driven Cross-Modal Interaction**. To support natural, multimodal communication and interaction, we develop a speech-grounded multimodal data construction pipeline that ensures both linguistic fluency and semantic fidelity in voice-based interactions, including 10+ authentic voices and tones.
 
 Based on ***FysicsWorld***, we extensively evaluate various advanced models, including Omni-LLMs, MLLMs, modality-specific models, and unified understanding–generation models. By establishing a unified benchmark and highlighting key capability gaps, FysicsWorld provides not only a foundation for evaluating emerging multimodal systems but also a roadmap for the next generation of full-modality architectures capable of genuinely holistic perception, reasoning, and interaction.