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---
license: cc-by-nc-sa-4.0
pretty_name: 'AraDiCE -- Culture'
dataset_info:
- config_name: Lebanon
splits:
- name: test
num_examples: 30
- config_name: Egypt
splits:
- name: test
num_examples: 30
- config_name: Syria
splits:
- name: test
num_examples: 30
- config_name: Palestine
splits:
- name: test
num_examples: 30
- config_name: Jordan
splits:
- name: test
num_examples: 30
- config_name: Qatar
splits:
- name: test
num_examples: 30
configs:
- config_name: Lebanon
data_files:
- split: test
path: lebanon/LEBANON.json
- config_name: Egypt
data_files:
- split: test
path: egypt/EGYPT.json
- config_name: Syria
data_files:
- split: test
path: syria/SYRIA.json
- config_name: Palestine
data_files:
- split: test
path: Palestine/PALESTINE.json
- config_name: Jordan
data_files:
- split: test
path: jordan/JORDAN.json
- config_name: Qatar
data_files:
- split: test
path: qatar/QATAR.json
---
# AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs
## Overview
The **AraDiCE** dataset is designed to evaluate dialectal and cultural capabilities in large language models (LLMs). The dataset consists of post-edited versions of various benchmark datasets, curated for validation in cultural and dialectal contexts relevant to Arabic. In this repository we show the cultural split of the data
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TO DO:
- **licenses_by-nc-sa_4.0_legalcode.txt** License information.
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## Evaluation
We have used [lm-harness](https://github.com/EleutherAI/lm-evaluation-harness) eval framework to for the benchmarking. We will soon release them. Stay tuned!!
## License
The dataset is distributed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)**. The full license text can be found in the accompanying `licenses_by-nc-sa_4.0_legalcode.txt` file.
## Citation
Please find the paper <a href="https://arxiv.org/pdf/2409.11404" target="_blank" style="margin-right: 15px; margin-left: 10px">here.</a>
```
@article{mousi2024aradicebenchmarksdialectalcultural,
title={{AraDiCE}: Benchmarks for Dialectal and Cultural Capabilities in LLMs},
author={Basel Mousi and Nadir Durrani and Fatema Ahmad and Md. Arid Hasan and Maram Hasanain and Tameem Kabbani and Fahim Dalvi and Shammur Absar Chowdhury and Firoj Alam},
year={2024},
publisher={arXiv:2409.11404},
url={https://arxiv.org/abs/2409.11404},
}
```
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