Update README.md

README.md

@@ -67,7 +67,7 @@ This is a dataset of scientific documents derived from [arXiv metadata](https://
 * The `default` subset contains the dataset with the document categories as classes in the form of lists of strings. The categories are ordered hierarchically according to the [arXiv category taxonomy](https://arxiv.org/category_taxonomy). In this dataset, the `->` symbols indicate a `parent->child` relationship between categories that can be linked and create a path from the root to the leaf node. For classification, you can either use the complete paths as classes or just parse the respective leaf nodes as classes, resulting in the same (abbreviated) categories.
 * The `arxiv_category_descriptions` subset contains the tags, names, and textual descriptions of the leaf nodes from the [arXiv category taxonomy](https://arxiv.org/category_taxonomy).
 
-📄 Paper: [Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes (ICNLSP 2024)](#)
+📄 Paper: [Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes (ICNLSP 2024)](https://arxiv.org/abs/2410.05770)
 
 💻 Code: [https://github.com/sebischair/FusionSent](https://github.com/sebischair/FusionSent)
 
@@ -89,10 +89,13 @@ MIT
 ## Citation information
 When citing our work in academic papers and theses, please use this BibTeX entry:
 ``` 
-@article{...,
-  title={...},
-  author={...},
-  journal={...},
-  year={...}
+@misc{schopf2024efficientfewshotlearningmultilabel,
+      title={Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes}, 
+      author={Tim Schopf and Alexander Blatzheim and Nektarios Machner and Florian Matthes},
+      year={2024},
+      eprint={2410.05770},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2410.05770}, 
 }
 ```