Update README.md

README.md

@@ -137,7 +137,7 @@ Data Labeling for Evaluation Datasets:
 ### LiveCodeBench (20240801-20250201)
 
 | Models | Pass@1 |
-|--------------|------------|
+|:--------------|:------------|
 | R1-Distill-Qwen-7B | 37.6 |
 | OpenCodeReasoning-Distill-Qwen-7B-Instruct | 51.3 | 
 
@@ -174,3 +174,19 @@ NVIDIA believes Trustworthy AI is a shared responsibility and we have establishe
 For more detailed information on ethical considerations for this model, please see the Model Card++ [Explainability](./EXPLAINABILITY.md), [Bias](./BIAS.md), [Safety & Security](./SAFETY_and_SECURITY.md), and [Privacy](./PRIVACY.md) Subcards.
 
 Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).
+
+
+## Citation
+
+If you find the data useful, please cite:
+```
+@article{ahmad2025opencodereasoning,
+      title={OpenCodeReasoning: Advancing Data Distillation for Competitive Coding}, 
+      author={Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, Aleksander Ficek, Siddhartha Jain, Jocelyn Huang, Vahid Noroozi, Boris Ginsburg},
+      year={2025},
+      eprint={2504.01943},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2504.01943}, 
+}
+