Update README.md

README.md

@@ -171,17 +171,32 @@ labels = predictions[0]['labels']
 
 ## 📄 Citation
 
-If you use our models, datasets, or methodology in your research, please cite our paper:
+If you use our models, datasets, or methodology in your research, please cite our papers.
 
-```bibtex
+For the IROS 2025 conference version, which primarily focuses on YOLO models and represents an earlier conference publication, please cite:
+```
+@inproceedings{he2025mitigatinghallucinationsyolobasedobject,
+      title={Mitigating Hallucinations in YOLO-based Object Detection Models: A Revisit to Out-of-Distribution Detection},
+      author={Weicheng He and Changshun Wu and Chih-Hong Cheng and Xiaowei Huang and Saddek Bensalem},
+      booktitle={Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
+      year={2025},
+      note={Accepted to IROS 2025},
+      eprint={2503.07330v2},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2503.07330v2}
+}
+```
+For the journal version, which expands the methodology to Faster-RCNN and RT-DETR, includes an automated data curation pipeline, and provides an in-depth analysis of the approach, please cite:
+```
 @inproceedings{wu2025revisitingoutofdistributiondetectionrealtime,
       title={Revisiting Out-of-Distribution Detection in Real-time Object Detection: From Benchmark Pitfalls to a New Mitigation Paradigm}, 
       author={Changshun Wu and Weicheng He and Chih-Hong Cheng and Xiaowei Huang and Saddek Bensalem},
       year={2025},
-      eprint={2503.07330},
+      eprint={2503.07330v3},
       archivePrefix={arXiv},
       primaryClass={cs.CV},
-      url={https://arxiv.org/abs/2503.07330}, 
+      url={https://arxiv.org/abs/2503.07330v3}, 
 }
 ```