Update README.md

README.md

@@ -128,6 +128,8 @@ base_model:
 News topic classification model based on [`xlm-roberta-large`](https://huggingface.co/FacebookAI/xlm-roberta-large)
 and fine-tuned on a [news corpus in 4 languages](http://hdl.handle.net/11356/1991) (Croatian, Slovenian, Catalan and Greek), annotated with the [top-level IPTC
 Media Topic NewsCodes labels](https://www.iptc.org/std/NewsCodes/treeview/mediatopic/mediatopic-en-GB.html).
+The development and evaluation of the model is described in the paper
+[LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification](https://doi.org/10.1109/ACCESS.2025.3544814) (Kuzman and Ljubešić, 2025).
 
 The model can be used for classification into topic labels from the 
 [IPTC NewsCodes schema](https://iptc.org/std/NewsCodes/guidelines/#_what_are_the_iptc_newscodes) and can be
@@ -316,15 +318,19 @@ model_args ={
 
 ## Citation
 
-Paper with the details on the model is currently in submission. If you use the model, please cite [this paper](https://arxiv.org/abs/2411.19638):
+If you use the model, please cite [this paper](https://doi.org/10.1109/ACCESS.2025.3544814):
 
 ```
-@article{kuzman2024llmteacherstudent,
-      title={{LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification}}, 
-      author={Kuzman, Taja and Ljube{\v{s}}i{\'c}, Nikola},
-      journal={arXiv preprint arXiv:2411.19638},
-      year={2024}
-}
+@ARTICLE{10900365,
+  author={Kuzman, Taja and Ljubešić, Nikola},
+  journal={IEEE Access}, 
+  title={LLM Teacher-Student Framework for Text Classification With No Manually Annotated Data: A Case Study in IPTC News Topic Classification}, 
+  year={2025},
+  volume={},
+  number={},
+  pages={1-1},
+  keywords={Data models;Annotations;Media;Manuals;Multilingual;Computational modeling;Training;Training data;Transformers;Text categorization;Multilingual text classification;IPTC;large language models;LLMs;news topic;topic classification;training data preparation;data annotation},
+  doi={10.1109/ACCESS.2025.3544814}}
 ```
 
 ## Funding