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Model: CWRUSafetyLab/Qwen2.5-1.5B-Instruct-EASE
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+base_model:
+- Qwen/Qwen2.5-1.5B-Instruct
+tags:
+- safety
+- alignment
+---
+
+# Qwen2.5-1.5B-Instruct-EASE
+This model is a fine-tuned version of [Qwen/Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) on the [EASE-SafetyReasoning](https://huggingface.co/datasets/HaonanShi/EASE-STAR41K-SafetyReasoning-10K) dataset.
+
+## Model description
+This is the safety reasoning aligned version model under the framework,[**EASE**](https://arxiv.org/pdf/2511.06512). We fine-tune Qwen2.5-1.5B-Instruct to enable **adaptive safety reasoning activation**. The model triggers explicit safety reasoning only under jailbreak-like semantics, while avoiding unnecessary safety reasoning on benign or general prompts. This design aims to maintain the model’s general task effectiveness and efficiency, while improving robustness against jailbreak attacks.
+
+## Intended use
+Safety-oriented research on:(1)Safety alignment, (2)Small language models and (3)Jailbreak robustness  
+
+## Citation
+If our model could help you, please cite our paper, thanks!🤗
+
+**EASE: Practical and Efficient Safety Alignment for Small Language Models(AAAI26)(oral)** 
+
+https://arxiv.org/pdf/2511.06512
+
+```bibtex
+@inproceedings{shi2026ease,
+  title={Ease: Practical and efficient safety alignment for small language models},
+  author={Shi, Haonan and Wang, Guoli and Ouyang, Tu and Wang, An},
+  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
+  volume={40},
+  number={44},
+  pages={37923--37931},
+  year={2026}
+}
+```
+

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