Update README.md

README.md

@@ -1,4 +1,6 @@
 ---
+base_model: LGAI-EXAONE/EXAONE-4.5-33B
+base_model_relation: quantized
 license: other
 license_name: exaone
 license_link: LICENSE
@@ -31,7 +33,7 @@ library_name: transformers
   <a href="https://www.lgresearch.ai/blog/view?seq=641" style="text-decoration: none;">
     <img src="https://img.shields.io/badge/📝-Blog-E343BD?style=for-the-badge" alt="Blog">
   </a>
-  <a href="https://github.com/LG-AI-EXAONE/EXAONE-4.5/blob/main/assets/Technical_Report__EXAONE_4_5.pdf" style="text-decoration: none;">
+  <a href="http://arxiv.org/abs/2604.08644" style="text-decoration: none;">
     <img src="https://img.shields.io/badge/📑-Technical_Report-684CF4?style=for-the-badge" alt="Technical Report">
   </a>
   <a href="https://github.com/LG-AI-EXAONE/EXAONE-4.5" style="text-decoration: none;">
@@ -54,7 +56,7 @@ Integrating a dedicated visual encoder into the existing EXAONE 4.0 framework, w
 EXAONE 4.5 features 33 billion parameters in total, including 1.2 billion parameters from the vision encoder. 
 EXAONE 4.5 achieves competitive performance in general benchmark while outperforming SOTA models of similar size in document understanding and Korean contextual reasoning, inheriting powerful language capabilities from our previous language models.
 
-For more details, please refer to the [technical report](https://github.com/LG-AI-EXAONE/EXAONE-4.5/blob/main/assets/Technical_Report__EXAONE_4_5.pdf), [blog](https://www.lgresearch.ai/blog/view?seq=641) and [GitHub](https://github.com/LG-AI-EXAONE/EXAONE-4.5).
+For more details, please refer to the [technical report](http://arxiv.org/abs/2604.08644), [blog](https://www.lgresearch.ai/blog/view?seq=641) and [GitHub](https://github.com/LG-AI-EXAONE/EXAONE-4.5).
 
 
 ### Model Configuration
@@ -88,7 +90,7 @@ For more details, please refer to the [technical report](https://github.com/LG-A
 
 ## Evaluation Results
 
-The following table shows the benchmark results for the original EXAONE 4.5. Detailed evaluation results of the original model can be found in our [technical report](https://github.com/LG-AI-EXAONE/EXAONE-4.5/blob/main/assets/Technical_Report__EXAONE_4_5.pdf).
+The following table shows the benchmark results for the original EXAONE 4.5. Detailed evaluation results of the original model can be found in our [technical report](http://arxiv.org/abs/2604.08644).
 
 
 ### Vision-Language Tasks
@@ -772,7 +774,7 @@ The model is licensed under [EXAONE AI Model License Agreement 1.2 - NC](./LICEN
 @article{exaone-4.5,
   title={EXAONE 4.5 Technical Report},
   author={{LG AI Research}},
-  journal={arXiv preprint arXiv:XXXX.XXXXX},
+  journal={arXiv preprint arXiv:2604.08644},
   year={2026}
 }
 ```