fix: reflect feedbacks

Author: maestrojeong

README.md

@@ -15,17 +15,19 @@ Welcome to **NEXT-EVAL**, a comprehensive toolkit for the rigorous evaluation an
 > 📄 **NEXT-EVAL: Next Evaluation of Traditional and LLM Web Data Record Extraction** [\[https://arxiv.org/abs/2505.17125\]](https://arxiv.org/abs/2505.17125)
 
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![Contributions Welcome](https://img.shields.io/badge/Contributions-Welcome-brightgreen.svg?style=flat)](CONTRIBUTING.md)
-[![Paper](https://img.shields.io/badge/Read%20the%20Paper-blue)](https://arxiv.org/abs/2505.17125) 
+[![Paper](https://img.shields.io/badge/Read%20the%20Paper-blue)](https://arxiv.org/abs/2505.17125) [![Web Demo](https://img.shields.io/badge/Try%20Web%20Demo-green)](https://nextrows.com/next-eval)
 
-This library provides tools for generating web-to-table datasets, applying extraction techniques (both traditional and LLM-based), and evaluating them with a standardized framework. It is intended to advance benchmarking and reproducibility in web data extraction research.
-
-## 🌐 Try the Web Demo
+## 🎥 Demo Video
 
-Experience NEXT-EVAL in action! Try our interactive web demo where you can upload HTML files or fetch live URLs to preprocess HTML in three different ways (Slim HTML, Hierarchical JSON, and Flat JSON) and compare traditional algorithms with LLM-based extraction methods:
+<p align="center">
+  <a href="https://www.youtube.com/watch?v=1TIeY08pX4I">
+    <img src="https://img.youtube.com/vi/1TIeY08pX4I/maxresdefault.jpg" alt="NEXT-EVAL Demo Video" width="600">
+  </a>
+</p>
 
-[![Launch Web Demo](https://img.shields.io/badge/Launch%20Web%20Demo-brightgreen?style=for-the-badge)](https://nextrows.com/next-eval)
+Experience NEXT-EVAL in action! Try our interactive web demo where you can upload HTML files or fetch live URLs to preprocess HTML in three different ways and compare extraction methods.
 
----
+This library provides tools for generating web-to-table datasets, applying extraction techniques (both traditional and LLM-based), and evaluating them with a standardized framework. It is intended to advance benchmarking and reproducibility in web data extraction research.
 
 ## 🏁 Getting Started
 
@@ -182,10 +184,6 @@ We welcome contributions to improve tool coverage, add datasets, or refine evalu
 
 ---
 
-# Gallery / Demo
-
-https://github.com/user-attachments/assets/a09ab8af-13d1-46bc-8ad1-8a114e1bb3db
-
 ## 📬 Contact
 
 Have questions or ideas? We'd love to hear from you. Contact us at [research@wordbricks.ai](mailto:research@wordbricks.ai)