Link to paper page

README.md

@@ -2,14 +2,15 @@
 language:
 - vi
 library_name: transformers
+license: mit
+pipeline_tag: question-answering
 tags:
 - SemViQA
 - question-answering
 - fact-checking
 - information-retrieval
-pipeline_tag: question-answering
-license: mit
 ---
+
 ## Model Description
 - **Developed by:** [SemViQA Research Team](https://huggingface.co/SemViQA)  
 - **Fine-tuned model:** [ViMRC](https://huggingface.co/nguyenvulebinh/vi-mrc-large)
@@ -17,7 +18,7 @@ license: mit
 - **Task:** Extractive QA, Evidence Extraction  
 - **Dataset:** [ISE-DSC01](https://codalab.lisn.upsaclay.fr/competitions/15497)
 
-This model is fine-tuned on [ViMRC](https://huggingface.co/nguyenvulebinh/vi-mrc-large) to evaluate its performance in comparison to our proposed approaches for Vietnamese fact-checking tasks.  
+This model is fine-tuned on [ViMRC](https://huggingface.co/nguyenvulebinh/vi-mrc-large) to evaluate its performance in comparison to our proposed approaches for Vietnamese fact-checking tasks.  For more details, see the [paper page](https://hf.co/papers/2503.00955).
 
 ## Using pre-trained model
 
@@ -53,4 +54,21 @@ print(evidence)
 *Built by Dien X. Tran*
 [![LinkedIn](https://img.shields.io/badge/LinkedIn-Profile-blue?logo=linkedin)](https://www.linkedin.com/in/xndien2004/)
 For more details, visit the project repository.
-[![GitHub stars](https://img.shields.io/github/stars/DAVID-NGUYEN-S16/SemViQA?style=social)](https://github.com/DAVID-NGUYEN-S16/SemViQA)
+[![GitHub stars](https://img.shields.io/github/stars/DAVID-NGUYEN-S16/SemViQA?style=social)](https://github.com/DAVID-NGUYEN-S16/SemViQA)
+
+
+## Citation
+
+If you use **SemViQA** in your research, please cite our work:
+
+```bibtex
+@misc{nguyen2025semviqasemanticquestionanswering,
+      title={SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking}, 
+      author={Nam V. Nguyen and Dien X. Tran and Thanh T. Tran and Anh T. Hoang and Tai V. Duong and Di T. Le and Phuc-Lu Le},
+      year={2025},
+      eprint={2503.00955},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://hf.co/papers/2503.00955}, 
+}
+```