README.md

---
dataset_info:
  features:
  - name: id
    dtype: string
  - name: message
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: image
    dtype: image
  splits:
  - name: train
    num_bytes: 5779284964.76
    num_examples: 44486
  - name: validation
    num_bytes: 708420205.08
    num_examples: 5560
  - name: test
    num_bytes: 744693334.836
    num_examples: 5562
  download_size: 3060451737
  dataset_size: 7232398504.676001
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- question-answering
- translation
- image-to-text
language:
- or
- en
pretty_name: Odia_VQA_Multimodal_Dataset
size_categories:
- 10K<n<100K
---
# Dataset Card for Odia_VQA_Multimodal_Dataset

### Dataset Summary

This dataset contains 27K English-Odia parallel instruction sets (Question-Answer) and 6k unique images. 
The dataset is useful for multimodal Visual Question-answering (VQA) in Odia and English. The instruction set format allows a multimodal large language model (LLM) fine-tuning.


The Odia data was annotated by the local language speakers and verified by linguists. 

### Supported Tasks and Leaderboards

Large Language Model (LLM)

### Languages

Odia, English

## Dataset Structure

JSON


### Licensing Information

This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg

### Citation Information

If you use the **OVQA** dataset, please consider giving 👏 and cite the following paper:


```
@inproceedings{parida2025ovqa,
title = {{OVQA: A Dataset for Visual Question Answering and Multimodal Research in Odia Language}},
author = {Parida, Shantipriya and Sahoo, Shashikanta and Sekhar, Sambit and Sahoo, Kalyanamalini and Kotwal, Ketan and Khosla, Sonal and Dash, Satya Ranjan and Bose, Aneesh and Kohli, Guneet Singh and Lenka, Smruti Smita and Bojar, Ondřej},
year = {2025},
note = {Accepted at the IndoNLP Workshop at COLING 2025} }
```

### Contributions

* Shantipriya Parida, Silo AI, Helsinki, Finland
* Shashikanta Sahoo, Government college of Engineering Kalahandi,India
* Sambit Sekhar, Odia Generative AI, India
* Satya Rankan Dash, KIIT University, India
* Kalyanamalini Sahoo, University of Artois, France
* Sonal Khosla, Odia Generative AI, India
* Aneesh Bose, Microsoft, India
* Guneet Singh Kohli, GreyOrange, India
* Ketan Kotwal, Idiap Research Institute, Switzerland
* Smruti Smita Lenka, Odia Generative AI, India 
* Ondřej Bojar, UFAL, Charles University, Prague, Czech Republic

### Point of Contact: 
**Shantipriya Parida, and Sambit Sekhar**