docs: update README.md

README.md

@@ -6,6 +6,9 @@ tags:
 - instruction-finetuning
 task_categories:
 - text-generation
+license: cc-by-nc-nd-4.0
+datasets:
+- IAAR-Shanghai/KAF-Dataset
 ---
 
 
@@ -20,7 +23,7 @@ xFinder-llama38it is a model specifically designed for key answer extraction in
 
 ## Model Sources
 - **Repository:** https://github.com/IAAR-Shanghai/xFinder
-- **Paper:** https://arxiv.org/abs/2405.11874
+- **Paper:** https://openreview.net/forum?id=7UqQJUKaLM
 
 ## Uses
 xFinder is primarily used to enhance the evaluation of LLMs by accurately extracting key answers from their outputs. It addresses the limitations of traditional regular expression (RegEx)-based extraction methods, which often fail to handle the diverse and complex outputs generated by LLMs. xFinder improves the reliability of model assessments across various tasks.
@@ -31,10 +34,12 @@ xFinder-llama38it is fine-tuned from Llama3-8B-Instruct. The training data consi
 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}
 }
 ```