Update README.md

README.md

@@ -246,10 +246,28 @@ nomic-embed-text-v2-moe performance on BEIR at 768 dimension and truncated to 25
 - Incorporates Matryoshka representation learning for dimension flexibility
 - Training includes both weakly-supervised contrastive pretraining and supervised finetuning
 
+For more details, please check out the [blog post](https://www.nomic.ai/blog/posts/nomic-embed-text-v2) and [technical report](https://www.arxiv.org/abs/2502.07972).
+
 
 
 ## Join the Nomic Community
 
 - Nomic: [https://nomic.ai](https://nomic.ai)
 - Discord: [https://discord.gg/myY5YDR8z8](https://discord.gg/myY5YDR8z8)
-- Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)
+- Twitter: [https://twitter.com/nomic_ai](https://twitter.com/nomic_ai)
+
+# Citation
+
+If you find the model, dataset, or training code useful, please cite our work
+
+```bibtex
+@misc{nussbaum2025trainingsparsemixtureexperts,
+      title={Training Sparse Mixture Of Experts Text Embedding Models}, 
+      author={Zach Nussbaum and Brandon Duderstadt},
+      year={2025},
+      eprint={2502.07972},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2502.07972}, 
+}
+```