Update README.md

README.md

@@ -14,16 +14,15 @@ configs:
 <p><strong>Hierarchical Graph Dataset for Malware Analysis with Function Call Graphs and Control Flow Graphs</strong></p>
 
 
- <img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Datasets-yellow" alt="Hugging Face" />
+<a href="https://arxiv.org/pdf/2509.02113"><img src="https://img.shields.io/badge/arXiv-2509.02113-b31b1b.svg" alt="arXiv" /></a>
+                <img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Datasets-yellow" alt="Hugging Face" />
                 <img src="https://img.shields.io/badge/Dataset-6.17GB-blue" alt="Dataset Size" />
-                <img src="https://img.shields.io/badge/Samples-595K%20FCGs-green" alt="Function Call Graphs" />
-                <img src="https://img.shields.io/badge/CFGs-200M%2B-brightgreen" alt="Control Flow Graphs" />
                 <img src="https://img.shields.io/badge/Period-2012--2022-orange" alt="Time Period" />
                 <img src="https://img.shields.io/badge/License-CC--BY--NC--SA-red" alt="License" />
 
 A comprehensive hierarchical graph-based dataset for malware analysis and detection.
 
-[Overview](#overview) • [Dataset Statistics](#dataset-statistics) • [Interactive Explorer](#interactive-visualization) • [Download](#download-dataset) 
+[Overview](#overview) • [Interactive Explorer](#interactive-visualization) • [Download](#download-dataset) 
 
 </div>
 
@@ -33,33 +32,15 @@ A comprehensive hierarchical graph-based dataset for malware analysis and detect
 
 Graph-based methods have shown great promise in malware analysis, yet the lack of large-scale, hierarchical graph datasets limits further advances in this field. This hierarchical design facilitates the development of robust detection models that are more resilient to obfuscation, model aging, and malware evolution.
 
-<div align="center">
-
-![Dataset Overview](https://raw.githubusercontent.com/hzcheney/HiGraph/refs/heads/master/assets/overview.png)
-
-</div>
 
 ### Key Features
 
 - 🔍 **Hierarchical Graph Structure**: Two-level representation with FCGs and CFGs
-- 📈 **Large Scale**: 200M+ Control Flow Graphs and 595K+ Function Call Graphs
+- 📈 **Large Scale**: 200M+ Control Flow Graphs and 499K+ Function Call Graphs
 - 🏷️ **Rich Semantic Information**: Preserves crucial structural details for malware analysis
 - 📊 **Comprehensive Coverage**: 11-year temporal span (2012-2022)
 - 🎯 **Benchmark Ready**: Designed for advancing hierarchical graph learning in cybersecurity
 
-## Dataset Statistics
-
-<div align="center">
-
-
-
-| Class | Time Period | # Apps | **Function Call Graph** || **Control Flow Graph** |||
-|-------|-------------|--------|---------------------|--|--------------------|--|--|
-|       |             |        | **Avg # Nodes** | **Avg # Edges** | **# Graphs** | **Avg # Nodes** | **Avg # Edges** |
-| **Malicious** | 2012.01-2022.12 | 57,184 | 266.48 | 491.67 | 6,925,406 | 12.29 | 14.94 |
-| **Benign** | 2012.01-2022.12 | 538,027 | 791.54 | 1,414.51 | 194,866,679 | 12.17 | 13.94 |
-
-</div>
 
 ## Interactive Visualization
 
@@ -71,9 +52,6 @@ Explore the hierarchical structure of malware samples through our interactive vi
 
 *Click to explore the complete dataset structure and sample graphs*
 
-![Sample Function Call Graph](https://raw.githubusercontent.com/hzcheney/HiGraph/refs/heads/master/assets/explorer.png)
-*Sample Function Call Graph (FCG) visualization*
-
 </div>
 
 ## Download Dataset
@@ -89,6 +67,19 @@ Access the complete HiGraph dataset through multiple platforms:
 
 </div>
 
+## Citation
+
+If you find HiGraph useful in your research, please cite:
+
+```
+@article{chen2025higraph,
+  title={HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis},
+  author={Chen, Han and Wang, Hanchen and Chen, Hongmei and Zhang, Ying and Qin, Lu and Zhang, Wenjie},
+  journal={arXiv preprint arXiv:2509.02113},
+  year={2025}
+}
+```
+
 ## Requirements
 - Python >= 3.9
 - torch==2.6.0
@@ -102,4 +93,4 @@ pip install -r requirements.txt
 
 ## 📄 License
 
-This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA)** license. See the [LICENSE](LICENSE) file for details.
+This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA)** license. See the [LICENSE](LICENSE) file for details.