Update README.md

README.md

@@ -17,6 +17,14 @@ tags:
 
 This is a fine-tuned BERT-based language model to classify NLP-related research papers as "Survey" or "Non-Survey" papers. The model is fine-tuned on a dataset of 787 survey and 11,805 non-survey papers from the ACL Anthology and the arXiv cs.CL category. Prior to fine-tuning, the model is initialized with weights from [malteos/scincl](https://huggingface.co/malteos/scincl).
 
+## This model was trained during our work on the Natural Language Processing Knowledge Graph (NLP-KG)
+ 
+🖥️ NLP-KG web application: [https://nlpkg.sebis.cit.tum.de](https://nlpkg.sebis.cit.tum.de)
+
+📄 Paper: [https://arxiv.org/abs/2406.15294](https://arxiv.org/abs/2406.15294)  
+
+📽️ Demo video: [https://youtu.be/-F529f4hmYo](https://youtu.be/-F529f4hmYo)
+
 
 ## How to use the fine-tuned model
 
@@ -46,4 +54,19 @@ The model was evaluated on 20% test data.
 * **F1:** 84.35
 * **Precision:** 82.38
 * **Recall:** 86.53
-* **Accuracy:** 98.04
+* **Accuracy:** 98.04
+
+
+## Citation information
+When citing our work in academic papers and theses, please use this BibTeX entry:
+``` 
+@misc{schopf2024nlpkgexploratorysearchscientific,
+      title={NLP-KG: A System for Exploratory Search of Scientific Literature in Natural Language Processing}, 
+      author={Tim Schopf and Florian Matthes},
+      year={2024},
+      eprint={2406.15294},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2406.15294}, 
+}
+```