Update README.md

README.md

@@ -54,6 +54,7 @@ license_link: LICENSE
   - [Training](#training)
   - [Limitations](#limitations)
 - [Why Yi-VL?](#why-yi-vl)
+  - [Tech report](#tech-report)
   - [Benchmarks](#benchmarks)
   - [Showcases](#showcases)
 - [How to use Yi-VL?](#how-to-use-yi-vl)
@@ -159,7 +160,23 @@ This is the initial release of the Yi-VL, which comes with some known limitation
 - Other limitations of the Yi LLM.
 
 # Why Yi-VL?
-  
+
+## Tech report
+
+For detailed capabilities of the Yi series model, see [Yi: Open Foundation Models by 01.AI](https://arxiv.org/abs/2403.04652).
+
+### Citation
+```
+@misc{ai2024yi,
+    title={Yi: Open Foundation Models by 01.AI},
+    author={01. AI and : and Alex Young and Bei Chen and Chao Li and Chengen Huang and Ge Zhang and Guanwei Zhang and Heng Li and Jiangcheng Zhu and Jianqun Chen and Jing Chang and Kaidong Yu and Peng Liu and Qiang Liu and Shawn Yue and Senbin Yang and Shiming Yang and Tao Yu and Wen Xie and Wenhao Huang and Xiaohui Hu and Xiaoyi Ren and Xinyao Niu and Pengcheng Nie and Yuchi Xu and Yudong Liu and Yue Wang and Yuxuan Cai and Zhenyu Gu and Zhiyuan Liu and Zonghong Dai},
+    year={2024},
+    eprint={2403.04652},
+    archivePrefix={arXiv},
+    primaryClass={cs.CL}
+}
+```
+
 ## Benchmarks
 
 Yi-VL outperforms all existing open-source models in [MMMU](https://mmmu-benchmark.github.io) and [CMMMU](https://cmmmu-benchmark.github.io/), two advanced benchmarks that include massive multi-discipline multimodal questions (based on data available up to January 2024).