Update README.md

README.md

@@ -112,4 +112,44 @@ ds_ner_ru_train = load_dataset("tvbat/SciMDIX", "ner_re", split="train_ru")
 print(ds_ner_ru_train[0])
 
 # Load the Kazakh Test split for Aspects
-ds_asp_kz_test = load_dataset("tvbat/SciMDIX", "aspects", split="test_kz")
+ds_asp_kz_test = load_dataset("tvbat/SciMDIX", "aspects", split="test_kz")
+```
+
+## Repository
+
+The code, models, and additional resources related to this dataset can be found in our [GitHub repository](https://github.com/tvbat/sci-text-miner-scimdix/tree/main)
+
+## Citation
+
+If you use the **SciMDIX** dataset in your research, please cite our papers:
+
+1. Batura T., Yerimbetova A., Mukazhanov N., Shvarts N., Sakenov B., Turdalyuly M. [Information Extraction from Multi-Domain Scientific Documents: Methods and Insights](https://doi.org/10.3390/app15169086). Applied Sciences. MDPI. 2025. V.15, 9086.
+
+```bibtex
+@article{scimdix2025,
+  author = {Batura, Tatiana and Yerimbetova, Aigerim and Mukazhanov, Nurzhan and Shvarts, Nikita and Sakenov, Bakzhan and Turdalyuly, Mussa},
+  title = {Information Extraction from Multi-Domain Scientific Documents: Methods and Insights},
+  journal = {Applied Sciences},
+  volume = {15},
+  year = {2025},
+  number = {16},
+  article-number = {9086},
+  publisher = {MDPI},
+  doi = {https://doi.org/10.3390/app15169086}
+}
+```
+
+2. Shvarts N., Batura T., Mukazhanov N., Yerimbetova A., Turdalyuly M., Sakenov B. [SciMDIX: A dataset for aspect extraction from multi-domain scientific documents in Kazakh and Russian](https://doi.org/10.1016/j.procs.2026.01.056). *Procedia Computer Science*. 2026. V. 275, pp.474-483.
+
+```bibtex
+@article{scimdix2026,
+  title={SciMDIX: A dataset for aspect extraction from multi-domain scientific documents in Kazakh and Russian},
+  author={Shvarts, Nikita and Batura, Tatiana and Mukazhanov, Nurzhan and Yerimbetova, Aigerim and Turdalyuly, Mussa and Sakenov, Bakzhan},
+  journal={Procedia Computer Science},
+  volume={275},
+  pages={474--483},
+  year={2026},
+  publisher={Elsevier},
+  doi = {https://doi.org/10.1016/j.procs.2026.01.056}
+}
+```