Update README.md

README.md

@@ -2,4 +2,18 @@
 
 This is the pre-trained policy model weights for our novel method, Constrained Initial Representations (CIR).
 
-The results are grouped into each environment and seed. One can directly load the policy weights from the corresponding directory
+The results are grouped into each environment and seed. One can directly load the policy weights from the corresponding directory
+
+One can find our papers [here](https://arxiv.org/pdf/2602.11800)
+
+# Citation
+
+If you find our work interesting or use our work in your paper, please consider citing our paper:
+```
+@article{lyu2026temporal,
+  title={Temporal Difference Learning with Constrained Initial Representations},
+  author={Lyu, Jiafei and Yang, Jingwen and Qiao, Zhongjian and Liu, Runze and Liu, Zeyuan and Ye, Deheng and Lu, Zongqing and Li, Xiu},
+  journal={arXiv preprint arXiv:2602.11800},
+  year={2026}
+}
+```