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README.md

@@ -22,7 +22,7 @@ datasets:
 
 # CodeScout-14B
 
-[📄 Paper](https://arxiv.org/abs/2507.02875) • [💻 Code](https://github.com/OpenHands/codescout) • [🤗 Collection](https://huggingface.co/collections/OpenHands/codescout-69b9a6adcf21f348f4db937f)
+[📄 Paper](https://arxiv.org/abs/XXXX.XXXXX) • [💻 Code](https://github.com/OpenHands/codescout) • [🤗 Collection](https://huggingface.co/collections/OpenHands/codescout-69b9a6adcf21f348f4db937f)
 
 **Strongest CodeScout model — open-source SOTA on SWE-Bench code localization.**
 
@@ -99,7 +99,7 @@ CodeScout-14B is designed for **repository-level code localization**: given a Gi
 @article{sutawika2025codescout,
   title={CodeScout: An Effective Recipe for Reinforcement Learning of Code Search Agents},
   author={Sutawika, Lintang and Soni, Aditya Bharat and R R, Bharath Sriraam and Gandhi, Apurva and Yassine, Taha and Vijayvargiya, Sanidhya and Li, Yuchen and Zhou, Xuhui and Zhang, Yilin and Maben, Leander Melroy and Neubig, Graham},
-  journal={arXiv preprint arXiv:2507.02875},
+  journal={arXiv preprint arXiv:XXXX.XXXXX},
   year={2025}
 }
 ```