update paper link

README.md

@@ -22,7 +22,7 @@ library_name: transformers
 ## What's New
 - [2025.09.05] **MiniCPM4.1** series are released! This series is a hybrid reasoning model, which can be used in
 both deep reasoning mode and non-reasoning mode. 🔥🔥🔥
-- [2025.06.06] **MiniCPM4** series are released! This model achieves ultimate efficiency improvements while maintaining optimal performance at the same scale! It can achieve over 5x generation acceleration on typical end-side chips! You can find technical report [here](https://github.com/OpenBMB/MiniCPM/tree/main/report/MiniCPM_4_Technical_Report.pdf).🔥🔥🔥
+- [2025.06.06] **MiniCPM4** series are released! This model achieves ultimate efficiency improvements while maintaining optimal performance at the same scale! It can achieve over 5x generation acceleration on typical end-side chips! You can find technical report [here](https://arxiv.org/abs/2506.07900).🔥🔥🔥
 
 ## MiniCPM4 and MiniCPM4.1 Series
 MiniCPM4 and MiniCPM4.1 series are highly efficient large language models (LLMs) designed explicitly for end-side devices, which achieves this efficiency through systematic innovation in four key dimensions: model architecture, training data, training algorithms, and inference systems.
@@ -335,7 +335,7 @@ MiniCPM4 is pre-trained on 32K long texts and achieves length extension through
 - This repository and MiniCPM models are released under the [Apache-2.0](https://github.com/OpenBMB/MiniCPM/blob/main/LICENSE) License. 
 
 ## Citation
-- Please cite our [paper](https://github.com/OpenBMB/MiniCPM/tree/main/report/MiniCPM_4_Technical_Report.pdf) if you find our work valuable.
+- Please cite our [paper](https://arxiv.org/abs/2506.07900) if you find our work valuable.
 
 ```bibtex
 @article{minicpm4,