Update README.md

README.md

@@ -14,4 +14,37 @@ model-index:
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-Base Model of RedCoder
+# REDCODER: Automated Multi-Turn Red Teaming for Code LLMs
+
+> 🔬 A model fine-tuned for adversarial multi-turn prompt generation to induce vulnerabilities in Code LLMs.  
+> 📄 [[arXiv:2507.22063](https://arxiv.org/pdf/2507.22063)] • 🧠 
+
+---
+
+
+## 🧠 Model Summary
+
+**REDCODER** is a red-teaming LLM trained to engage target Code LLMs in multi-turn conversations that gradually steer them into generating **CWE vulnerabilities** (e.g., Such as path traversal, SQL injection, etc.).
+
+This model is designed to support:
+- ⚔️ **Red-teaming evaluations** for Code LLMs
+- 🧪 **Security benchmarking** of model guardrails and filters
+- 🧩 **Multi-turn adversarial prompt generation** in research settings
+
+> ⚠️ This model should not be used to generate real-world exploits. Its intended use is for research, safety evaluation, and secure LLM development.
+
+---
+
+
+If you find this work useful, please cite:
+
+```bibtex
+@article{mo2025redcoder,
+  title   = {REDCODER: Automated Multi-Turn Red Teaming for Code LLMs},
+  author  = {Wenjie Jacky Mo and Qin Liu and Xiaofei Wen and Dongwon Jung and
+             Hadi Askari and Wenxuan Zhou and Zhe Zhao and Muhao Chen},
+  journal = {arXiv preprint arXiv:2507.22063},
+  year    = {2025}
+}
+```
+