Update dataset card with paper link, task categories and usage

Hi! I'm Niels from the Hugging Face community science team. This PR improves the dataset card for Interaction2Code by:
- Updating the task category to `image-text-to-text`.
- Adding links to the paper on Hugging Face Papers, the official project page, and the GitHub repository.
- Providing a description of the dataset structure and an example of the interaction metadata (`action.json`).
- Adding a sample usage section with a code snippet for generation as found in the GitHub README.
- Including the BibTeX citation for the ASE 2025 paper.

README.md

@@ -1,8 +1,77 @@
 ---
-task_categories:
-- text-generation
 language:
 - en
 size_categories:
 - n<1K
----
+task_categories:
+- image-text-to-text
+---
+
+# Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping
+
+[**Project Page**](https://webpai.github.io/Interaction2Code/) | [**Paper**](https://huggingface.co/papers/2411.03292) | [**GitHub**](https://github.com/WebPAI/Interaction2Code)
+
+Interaction2Code is the first systematic investigation and benchmark for Multimodal Large Language Models (MLLMs) in generating **interactive** webpages. While existing benchmarks focus on static UI-to-code tasks, Interaction2Code encompasses 127 unique webpages and 374 distinct interactions across 15 webpage types and 31 interaction categories to evaluate dynamic interaction generation.
+
+## Dataset Structure
+
+The full dataset contains 127 subfolders, each corresponding to a unique webpage. Each subfolder contains:
+
+- **Interactive Prototyping Images:** Screenshots representing the webpage states (e.g., `0.png` for the initial state, `1.png` for the state after an interaction).
+- **action.json:** A metadata file describing the interaction, including the source/destination images, tag types (e.g., button, image), and visual types (e.g., new component, color).
+
+### Example `action.json`
+```json
+{
+  "link": "https://salinaka-ecommerce.web.app/shop", 
+  "topic": "shop",
+  "framework": "react",
+  "1": {
+    "src": "0",
+    "dst": "1",
+    "tag type": [
+      "image",
+      "span"
+    ],
+    "visual type": [
+      "new component",
+      "text",
+      "position"
+    ]
+  }
+}
+```
+
+## Sample Usage
+
+Based on the official [GitHub repository](https://github.com/WebPAI/Interaction2Code), you can use the following snippet to generate interactive webpage code (ensure you have configured your API keys in `key.json` within the repo structure):
+
+```python
+# Assuming you are in the code/prompting directory of the repository
+from generate import generate_page
+
+# prompt_method: direct_prompt/cot_prompt/mark_prompt/critic_prompt
+generate_page(
+    path="../../sample/", 
+    web_number=1, 
+    interact_number=1, 
+    prompt_method="direct_prompt"
+)
+```
+
+## Citation
+
+If you find this benchmark or code useful, please consider citing the paper:
+
+```bibtex
+@INPROCEEDINGS{xiao2025interaction2code,
+  author={Xiao, Jingyu and Wan, Yuxuan and Huo, Yintong and Wang, Zixin and Xu, Xinyi and Wang, Wenxuan and Xu, Zhiyao and Wang, Yuhang and Lyu, Michael R.},
+  booktitle={2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025)}, 
+  title={Interaction2Code: Benchmarking MLLM-based Interactive Webpage Code Generation from Interactive Prototyping}, 
+  year={2025},
+  volume={},
+  number={},
+  pages={241-253},
+  doi={10.1109/ASE63991.2025.00028}
+}
+```