Add arxiv citation in README

README.md

@@ -12,6 +12,7 @@ datasets:
 # PCMind-2.1-Kaiyuan-2B (脑海-2.1-开元-2B)
 
 [![License](https://img.shields.io/badge/License-Apache-f5de53?&color=f5de53)](LICENSE)
+[![arXiv-2512.07612](https://img.shields.io/badge/arXiv-2512.07612-b31b1b.svg?style=flat)](https://arxiv.org/abs/2512.07612)
 
 PCMind-2.1-Kaiyuan-2B is a cutting-edge, **fully open-source language model** (i.e., open dataset) trained on a Ascend 910A cluster. 
 With 1.4B non-embedding parameters and training on 2.2 trillion tokens, 
@@ -23,6 +24,8 @@ it achieves performance competitive with current state-of-the-art fully open mod
 
 The dataset used to train Kaiyuan-2B is published at <https://huggingface.co/datasets/thu-pacman/PCMind-2.1-Kaiyuan-2B>.
 
+The _PCMind-2.1-Kaiyuan-2B Technical Report_ is published at <https://arxiv.org/abs/2512.07612>. 
+
 ## Introduction
 
 Our data preprocessing and pre-training pipeline is designed for enhanced training efficiency and model quality, 
@@ -59,7 +62,19 @@ or to fine-tune the model for specific downstream applications.*
 
 ## Citation
 
-Our technical report is coming soon!
+Please cite [our technical report](https://arxiv.org/abs/2512.07612) if you use our model, dataset, or code.
+
+```bib
+@misc{luo2025pcmind21kaiyuan2btechnicalreport,
+  title={PCMind-2.1-Kaiyuan-2B Technical Report}, 
+  author={Kairong Luo and Zhenbo Sun and Xinyu Shi and Shengqi Chen and Bowen Yu and Yunyi Chen and Chenyi Dang and Hengtao Tao and Hui Wang and Fangming Liu and Kaifeng Lyu and Wenguang Chen},
+  year={2025},
+  eprint={2512.07612},
+  archivePrefix={arXiv},
+  primaryClass={cs.CL},
+  url={https://arxiv.org/abs/2512.07612},
+}
+```
 
 ## License