initialize

README.md

@@ -1,4 +1,18 @@
+---
+title: ViLaBench
+emoji: 🧠
+colorFrom: yellow
+colorTo: indigo
+sdk: static
+pinned: false
+license: apache-2.0
+short_description: Benchmark collection for Vision-Language Models (VLMs)
+---
+
+
+
 # ViLaBench
+
 This is a web project showcasing a collection of benchmarks for vision-language models. 
 
 These benchmark and result data are carefully compiled and merged from technical reports and official blogs of renowned multimodal models, including Google's Gemini series ([Gemini 2.5 Report](https://storage.googleapis.com/deepmind-media/gemini/gemini_v2_5_report.pdf)), OpenAI GPT series and OpenAI o series ([OpenAI o3 and o4-mini](https://openai.com/index/introducing-o3-and-o4-mini/)), [Seed1.5-VL](https://arxiv.org/pdf/2505.07062), [MiMo-VL](https://arxiv.org/pdf/2506.03569), [Kimi-VL](https://huggingface.co/moonshotai/Kimi-VL-A3B-Thinking-2506), [Qwen2.5-VL](https://arxiv.org/pdf/2502.13923), [InternVL3](https://arxiv.org/abs/2504.10479), and other leading models' official technical documentation.
@@ -22,15 +36,19 @@ This collection provides researchers and developers with a comprehensive, standa
 ## Local Usage
 
 1. Ensure `vilabench.csv` and `index.html` are in the same directory
+
 2. Use a local server to open the webpage (to avoid CORS issues):
+
    ```bash
    python3 -m http.server 8000
    ```
+
 3. Visit `http://localhost:8000` in your browser
 
 ## Data Format
 
 The CSV file contains the following columns:
+
 - Benchmark: Benchmark name
 - URL: Paper link
 - year: Publication year