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README.md

@@ -16,14 +16,12 @@ size_categories:
 
 <div style="display: flex; align-items: center;">
     <img src="https://huggingface.co/datasets/likaixin/MMCode/resolve/main/logo.png" alt="MMCode Logo" style="width: 50px;margin-right: 20px;"/>
-    <div style="display: flex; align-items: center; font-size: 40px; font-weight: bold;">MMCode (Preview v1.0)</div>
+    <div style="display: flex; align-items: center; font-size: 40px; font-weight: bold;">MMCode</div>
 </div>
 
-🚀 **MMCode is actively under development! If you find it useful and are interested in making it better and joining our team, please [drop an email](mailto:[email protected]). We'd love to hear from you!**
-
 ## Dataset Description
 MMCode is a multi-modal code generation dataset designed to evaluate the problem-solving skills of code language models in visually rich contexts (i.e. images). 
-It contains 3,548 questions paired with 6,622 images, derived from real-world programming challenges across 10 code competition websites, with Python solutions and tests provided. 
+It contains 3,548 questions paired with 6,620 images, derived from real-world programming challenges across 10 code competition websites, with Python solutions and tests provided. 
 The dataset emphasizes the extreme demand for reasoning abilities, the interwoven nature of textual and visual contents, and the occurrence of questions containing multiple images.
 
 ## Languages
@@ -65,7 +63,7 @@ Each problem includes a programming question paired with relevant images, Python
 ## Key Features
 - **Multi-Modal Challenges**: MMCode is the first work towards code generation combining textual and visual information, requiring models to interpret and integrate both modalities of data for problem-solving.
 
-- **Rich Diversity**: With 3,548 questions paired with 6,622 images, sourced from 10 different coding competition websites, the dataset offers a diverse range of real-world programming challenges.
+- **Rich Diversity**: With 3,548 questions paired with 6,620 images, sourced from 10 different coding competition websites, the dataset offers a diverse range of real-world programming challenges.
 
 - **Detailed Annotations**: The dataset includes detailed annotations for images, categorizing them into types `Data Structure`, `Geometry`, `3D`, `Demonstration`, `Math`, `Table`, `Pseudocode`, and `Others`, which allows for a detailed analysis of model performance across different visual information types.
 
@@ -207,7 +205,7 @@ Please contact us if there are data license issues.
 Please cite our work if you find it useful:
 ```
 @misc{li2024MMCode,
-  author = {Kaixin, Li and Yuchen, Tian and Qisheng, Hu},
+  author = {Kaixin, Li and Yuchen, Tian and Qisheng, Hu and Ziyang Luo and Wee Sun Lee},
   title = {MMCode: Evaluating Multi-Modal Code Language Models with Visually Rich Programming Problems},
   year = {2024},
   howpublished = {\url{https://github.com/Happylkx/MMCode}},