Update README.md

README.md

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-
-
 # Generative-VQA-V2-Curated
 
 A curated, balanced, and cleaned version of the VQA v2 dataset specifically optimized for **Generative Visual Question Answering**.
@@ -22,7 +20,7 @@ The primary goal of this curated set is to provide a "clean" signal for training
 * **Minimum Frequency per Answer:** 20
 * **Maximum Samples per Answer:** 600
 
-## 🛠 Curation Logic
+## Curation Logic
 
 The dataset was generated using the following filtering pipeline:
 
@@ -80,12 +78,47 @@ This dataset is a derivative work of the **VQA v2 Dataset** and the **COCO Datas
 * **Images:** [COCO Consortium (CC BY 4.0)](https://www.google.com/search?q=https://cocodataset.org/%23termsofuse)
 * **Annotations:** [VQA v2 (CC BY 4.0)](https://visualqa.org/download.html)
 
+## Citation
+
+If you use this dataset in your research or project, please cite it as follows:
+
+```bibtex
+@misc{devarajan_genvqa_2026,
+  author = {Devarajan},
+  title = {Generative-VQA-V2-Curated: A Balanced Dataset for Open-Ended VQA},
+  year = {2026},
+  publisher = {Hugging Face},
+  howpublished = {\url{[https://huggingface.co/datasets/Deva8/Generative-VQA-V2-Curated](https://huggingface.co/datasets/Deva8/Generative-VQA-V2-Curated)}}
+}
+```
+
+---
 license: mit
 task_categories:
 - visual-question-answering
 tags:
-- agent
-- code
-pretty_name: Vqa-Dataset for generative tasks
+- generative-vqa
+- multimodal
+- vqa-v2
+pretty_name: Generative-VQA-V2 (Curated)
 size_categories:
-- 10K<n<100K
+- 100K<n<1M
+configs:
+- data_files:
+    - split: train
+      path: 
+      - "metadata.csv"
+      - "gen_vqa_v2-images.zip"
+dataset_info:
+  features:
+    - name: image_id
+      dtype: int64
+    - name: question_id
+      dtype: int64
+    - name: question
+      dtype: string
+    - name: answer
+      dtype: string
+    - name: image_path
+      dtype: image  
+---