Update README.md

README.md

@@ -114,11 +114,12 @@ outputs = pipeline(
 print(outputs[0]["generated_text"][-1]['content'])
 ````
 
+We have added [a simple transformer-based script](https://huggingface.co/nvidia/OpenReasoning-Nemotron-7B/blob/main/genselect_hf.py) in this repo to illustrate GenSelect.  
+To learn how to use the models in GenSelect mode with NeMo-Skills, see our [documentation](https://nvidia.github.io/NeMo-Skills/releases/openreasoning/evaluation/).
+
 To use the model with GenSelect inference, we recommend following our 
-[reference implementation in NeMo-Skills](https://github.com/NVIDIA/NeMo-Skills/blob/main/nemo_skills/pipeline/genselect.py). 
-Alternatively, you can manually extract the summary from all solutions and use this 
-[prompt](https://github.com/NVIDIA/NeMo-Skills/blob/main/nemo_skills/prompt/config/openmath/genselect.yaml) for the math problems.
-We will add the prompt we used for the coding problems and a reference implementation soon!
+[reference implementation in NeMo-Skills](https://github.com/NVIDIA/NeMo-Skills/blob/main/nemo_skills/pipeline/genselect.py). Alternatively, you can manually extract the summary from all solutions and use this 
+[prompt](https://github.com/NVIDIA/NeMo-Skills/blob/main/nemo_skills/prompt/config/openmath/genselect.yaml) for the math problems. We will add the prompt we used for the coding problems and a reference implementation soon!
 
 You can learn more about GenSelect in these papers:
 * [AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset](https://arxiv.org/abs/2504.16891)
@@ -130,7 +131,7 @@ You can learn more about GenSelect in these papers:
 If you find the data useful, please cite:
 ```
 @article{ahmad2025opencodereasoning,
-      title={OpenCodeReasoning: Advancing Data Distillation for Competitive Coding}, 
+      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},
@@ -142,7 +143,7 @@ If you find the data useful, please cite:
 
 ```
 @misc{ahmad2025opencodereasoningiisimpletesttime,
-      title={OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique}, 
+      title={{OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique}}, 
       author={Wasi Uddin Ahmad and Somshubra Majumdar and Aleksander Ficek and Sean Narenthiran and Mehrzad Samadi and Jocelyn Huang and Siddhartha Jain and Vahid Noroozi and Boris Ginsburg},
       year={2025},
       eprint={2507.09075},
@@ -154,7 +155,7 @@ If you find the data useful, please cite:
 
 ```
 @misc{moshkov2025aimo2winningsolutionbuilding,
-      title={AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset}, 
+      title={{AIMO-2 Winning Solution: Building State-of-the-Art Mathematical Reasoning Models with OpenMathReasoning dataset}}, 
       author={Ivan Moshkov and Darragh Hanley and Ivan Sorokin and Shubham Toshniwal and Christof Henkel and Benedikt Schifferer and Wei Du and Igor Gitman},
       year={2025},
       eprint={2504.16891},
@@ -164,6 +165,16 @@ If you find the data useful, please cite:
 }
 ```
 
+```
+@inproceedings{toshniwal2025genselect,
+      title={{GenSelect: A Generative Approach to Best-of-N}},
+      author={Shubham Toshniwal and Ivan Sorokin and Aleksander Ficek and Ivan Moshkov and Igor Gitman},
+      booktitle={2nd AI for Math Workshop @ ICML 2025},
+      year={2025},
+      url={https://openreview.net/forum?id=8LhnmNmUDb}
+}
+```
+
 ## Additional Information:
 
 ### Deployment Geography: