neulab/PangeaBench-xgqa

---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: full_answer
dtype: string
- name: image_id
dtype: string
- name: image
dtype: image
splits:
- name: bn
num_bytes: 498517814
num_examples: 9666
- name: de
num_bytes: 498108367
num_examples: 9666
- name: en
num_bytes: 498078827
num_examples: 9666
- name: id
num_bytes: 498180441
num_examples: 9666
- name: ko
num_bytes: 498157980
num_examples: 9666
- name: pt
num_bytes: 498078408
num_examples: 9666
- name: ru
num_bytes: 498298164
num_examples: 9666
- name: zh
num_bytes: 498005624
num_examples: 9666
download_size: 2692912777
dataset_size: 3985425625
configs:
- config_name: default
data_files:
- split: bn
path: data/bn-*
- split: de
path: data/de-*
- split: en
path: data/en-*
- split: id
path: data/id-*
- split: ko
path: data/ko-*
- split: pt
path: data/pt-*
- split: ru
path: data/ru-*
- split: zh
path: data/zh-*
license: cc-by-4.0
task_categories:
- visual-question-answering
language:
- bn
- de
- en
- id
- ko
- pt
- ru
- zh
pretty_name: xgqa
size_categories:
- 10K<n<100K
---

# xGQA

### This is a clone of the `few_shot-test` split of the xGQA dataset

Please find the original repository here: https://github.com/adapter-hub/xGQA

If you use this dataset, please cite the original authors:

```bibtex
@inproceedings{pfeiffer-etal-2021-xGQA,
title={{xGQA: Cross-Lingual Visual Question Answering}},
author={ Jonas Pfeiffer and Gregor Geigle and Aishwarya Kamath and Jan-Martin O. Steitz and Stefan Roth and Ivan Vuli{\'{c}} and Iryna Gurevych},
booktitle = "Findings of the Association for Computational Linguistics: ACL 2022",
month = May,
year = "2022",
url = "https://arxiv.org/pdf/2109.06082.pdf",
publisher = "Association for Computational Linguistics",
}
```