QCRI/AraDiCE-OpenBookQA

---
license: cc-by-nc-sa-4.0
language:
- ar
pretty_name: 'AraDiCE -- OpenBookQA'
dataset_info:
- config_name: OBQA-eng
splits:
- name: test
num_examples: 497
- config_name: OBQA-msa
splits:
- name: test
num_examples: 497
- config_name: OBQA-lev
splits:
- name: test
num_examples: 497
- config_name: OBQA-egy
splits:
- name: test
num_examples: 497
configs:
- config_name: OBQA-eng
data_files:
- split: test
path: OBQA_eng/test.json
- config_name: OBQA-msa
data_files:
- split: test
path: OBQA_msa/test.json
- config_name: OBQA-lev
data_files:
- split: test
path: OBQA_lev/test.json
- config_name: OBQA-egy
data_files:
- split: test
path: OBQA_egy/test.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 present the OpenBookQA split of the data.

<!-- ## File/Directory

TO DO:

- **licenses_by-nc-sa_4.0_legalcode.txt** License information.
- **README.md** This file. -->
## 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},
}
```