docs: update README.md

README.md

@@ -32,10 +32,12 @@ xFinder-qwen1505 is fine-tuned from Qwen-1.5-0.5B. The training data consists of
 xFinder is evaluated on the fully human-annotated test and generalization sets of the KAF dataset. The results demonstrate significant improvements in extraction accuracy and robustness compared to traditional methods. For more details, please refer to the paper and try it out using the provided code.
 ## Citation
 ```
-@article{xFinder,
-      title={xFinder: Robust and Pinpoint Answer Extraction for Large Language Models}, 
-      author={Qingchen Yu and Zifan Zheng and Shichao Song and Zhiyu Li and Feiyu Xiong and Bo Tang and Ding Chen},
-      journal={arXiv preprint arXiv:2405.11874},
-      year={2024},
+@inproceedings{
+    xFinder,
+    title={xFinder: Large Language Models as Automated Evaluators for Reliable Evaluation},
+    author={Qingchen Yu and Zifan Zheng and Shichao Song and Zhiyu li and Feiyu Xiong and Bo Tang and Ding Chen},
+    booktitle={The Thirteenth International Conference on Learning Representations},
+    year={2025},
+    url={https://openreview.net/forum?id=7UqQJUKaLM}
 }
 ```