Update README.md

README.md

@@ -4,10 +4,79 @@ task_categories:
 - question-answering
 language:
 - sr
-file_format:
-  - parquet
 tags:
 - text
 - extractive-qa
 - generative-qa
----
+---
+
+# Serbian Question-Answering Datasets
+
+This repository provides multiple QA datasets in Serbian, suitable for training LLMs to answer questions, perform tasks, or function as chatbots.  
+
+## Datasets Overview
+
+1. **SQuAD-sr-md** – Manually corrected subset of SQuAD-sr (~7k corrected samples), for higher reliability and accuracy.  
+2. **SerbianQA-Gen** – Synthetic QA dataset (~74k samples) generated from encyclopedia articles, Wikipedia pages, and scientific abstracts. Organized into four sub-datasets:
+   - **PaSaz**  
+   - **Wikipedia**  
+   - **Sveznanje**  
+   - **Biblisha**
+
+---
+
+## Folder Structure
+
+```text
+QuestionAnswering/
+│
+├─ README.md
+├─ SQuAD-sr-md/
+│   └─ train.json
+├─ SerbianQA-Gen/
+│   ├─ PaSaz/
+│   │   └─ train.json
+│   ├─ Wikipedia/
+│   │   └─ train.json
+│   ├─ Sveznanje/
+│   │   └─ train.json
+│   └─ Biblisha/
+│       └─ train.json
+
+
+---
+
+## Dataset Viewer Links
+
+- **[SQuAD-sr-md](https://huggingface.co/datasets/JovanaR/SQuAD-sr-md?viewer=true)**  
+- **[SerbianQA-Gen / PaSaz](https://huggingface.co/datasets/JovanaR/PaSaz?viewer=true)**  
+- **[SerbianQA-Gen / Wikipedia](https://huggingface.co/datasets/JovanaR/Wikipedia?viewer=true)**  
+- **[SerbianQA-Gen / Sveznanje](https://huggingface.co/datasets/JovanaR/Sveznanje?viewer=true)**  
+- **[SerbianQA-Gen / Biblisha](https://huggingface.co/datasets/JovanaR/Biblisha?viewer=true)**  
+
+---
+
+## About the Work
+
+**Development of Serbian QA Datasets through Prompt-Based Generation and Human Validation**  
+*Jovana Rađenović, Olivera Kitanović, Ranka Stanković, Mihailo Škorić*  
+Faculty of Mining and Geology, University of Belgrade, Serbia  
+{jovana.radjenovic, olivera.kitanovic, ranka.stankovic, mihailo.skoric}@rgf.bg.ac.rs  
+
+> **Status:** Accepted, not yet published  
+
+Large Language Models (LLMs) rely on high-quality QA datasets. For Serbian, such datasets are scarce.  
+In this work, we systematically corrected and improved a subset of SQuAD-sr (~7k samples) and generated additional QA datasets (~74k samples) from multiple sources, providing reliable training data for Serbian QA models.
+
+---
+
+## Citation
+
+```bibtex
+@unpublished{Radjenovic2026SerbianQA,
+  title={Development of Serbian QA Datasets through Prompt-Based Generation and Human Validation},
+  author={Jovana Rađenović and Olivera Kitanović and Ranka Stanković and Mihailo Škorić},
+  year={2026},
+  note={Accepted, not yet published}
+}
+