Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+  - en
+  - zh
+base_model:
+  - Qwen/Qwen2.5-0.5B-Instruct
+tags:
+  - context compression
+  - sentence selection
+  - probing classifier
+  - attention probing
+  - RAG
+  - LongBench
+---
+
+# Sentinel Probing Classifier (Logistic Regression)
+
+This repository contains the sentence-level classifier used in **Sentinel**, a lightweight context compression framework introduced in our ACL 2025 paper:
+
+> **Sentinel: Attention Probing of Proxy Models for LLM Context Compression with an Understanding Perspective**  
+> Yong Zhang, Yanwen Huang, Ning Cheng, Yang Guo, Yun Zhu, Yanmeng Wang, Shaojun Wang, Jing Xiao  
+> 📄 [Paper (Arxiv 2025)](https://arxiv.org/abs/2303.08774) | 💻 [Code on GitHub](https://github.com/yzhangchuck/Sentinel)
+
+---
+
+## 🧠 What is Sentinel?
+
+**Sentinel** reframes LLM context compression as a lightweight attention-based *understanding* task. Instead of fine-tuning a full compression model, it:
+
+- Extracts **decoder attention** from a small proxy LLM (e.g., Qwen-2.5-0.5B)
+- Computes **sentence-level attention features**
+- Applies a **logistic regression (LR) classifier** to select relevant sentences
+
+This approach is efficient, model-agnostic, and highly interpretable.
+
+---
+
+## 📦 Files Included
+
+| File                    | Description                                  |
+|-------------------------|----------------------------------------------|
+| `sentinel_lr_model.pkl` | Trained logistic regression classifier       |
+| `sentinel_config.json`  | Feature extraction configuration             |
+
+---
+
+## 🚀 Usage
+
+Use this classifier on attention-derived feature vectors to predict sentence-level relevance scores:
+
+🛠 Feature extraction code and full pipeline available at:
+👉 https://github.com/yzhangchuck/Sentinel
+
+## 📈 Benchmark Results
+<p align="center">
+  <img src="longbench_gpt35.png" alt="LongBench GPT-3.5 Results" width="750"/>
+</p>
+
+
+<p align="center">
+  <img src="longbench_qwen7b.png" alt="LongBench Qwen Results" width="750"/>
+</p>
+
+
+## 📄 Citation
+Please cite us if you use this model:
+
+@misc{zhang2025sentinelattentionprobingproxy,
+      title={Sentinel: Attention Probing of Proxy Models for LLM Context Compression with an Understanding Perspective}, 
+      author={Yong Zhang and Yanwen Huang and Ning Cheng and Yang Guo and Yun Zhu and Yanmeng Wang and Shaojun Wang and Jing Xiao},
+      year={2025},
+      eprint={2505.23277},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2505.23277}, 
+}
+
+## 📬 Contact
+	•	📧 [email protected]
+	•	🔗 Project: https://github.com/yzhangchuck/Sentinel
+
+
+## 🔒 License
+
+Apache License 2.0 — Free for research and commercial use with attribution.