README.md

---
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task_categories:
- text-generation
---

## Dataset Card for m-ArenaHard-v2.0

This dataset is used in the paper [When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://huggingface.co/papers/2506.20544).

### Dataset Details

The m-ArenaHard-v2.0 dataset is a multilingual LLM evaluation set. This is built on the LMarena (formerly LMSYS) [arena-hard-auto-v2.0](https://github.com/lmarena/arena-hard-auto/tree/main/data/arena-hard-v2.0) test dataset. 
This dataset(containing 750 prompts) was filtered to "english" only prompts using the *papluca/xlm-roberta-base-language-detection* model resulting in 498 prompts. 
These filtered prompts were then translated into 22 languages by using an in-house state-of-the-art translation model resulting in a total test set of 11,454 multilingual prompts.

The 23 languages included in this dataset are :

- Arabic (ar)
- Chinese (zh)
- Czech (cs)
- Dutch (nl)
- English (en)
- French (fr)
- German (de)
- Greek (el)
- Hebrew (he)
- Hindi (hi)
- Indonesian (id)
- Italian (it)
- Japanese (ja)
- Korean (ko)
- Persian (fa)
- Polish (pl)
- Portuguese (pt)
- Romanian (ro)
- Russian (ru)
- Spanish (es)
- Turkish (tr)
- Ukrainian (uk)
- Vietnamese (vi)

## Load with Datasets
To load this dataset with Datasets, you'll need to install Datasets as 
`pip install datasets --upgrade`

and then use the following code:

```python
from datasets import load_dataset

dataset = load_dataset("CohereLabs/m-ArenaHard-v2.0", "en")
```

If you instead would like to load the entire dataset, you can concatenate them using the following code:
```python
from datasets import load_dataset, concatenate_datasets, get_dataset_config_names

moniker = 'CohereLabs/m-ArenaHard-v2.0'
dataset = concatenate_datasets([load_dataset(moniker,subset)['test'] for subset in get_dataset_config_names(moniker)])

```

## Dataset Structure
An instance of the data from the Korean subset looks as follows:
```python
{
'question_id': 'efe7a57ed35d476b',
 'category': 'hard_prompt',
 'subcategory': 'coding',
 'prompt': '깊게 숨을 들이쉬고 단계별로 생각해 보세요. 사용자의 데이터 기밀성을 보장하기 위해 사용자가 전체 하드 드라이브를 암호화할 수 있도록 돕는 프로그램을 설계하고 작성하세요.',
 'language': 'ko'
}
```

## Dataset Fields
The following are the fields in the dataset:

- question_id: a unique ID for the example (this will be the same across languages)
- category: prompt category from original dataset
- subcategory: finer-grained prompt category from original dataset
- prompt: text of the prompt (question or instruction)
- language: language of the prompt

All language subsets of the dataset share the same fields as above.

## Authorship
- Publishing Organization: Cohere Labs
- Industry Type: Not-for-profit - Tech
- Contact Details: https://cohere.com/research

## Licensing Information
This dataset can be used for any purpose, whether academic or commercial, under the terms of the Apache 2.0 License.

## Citation
```
@misc{khairi2025lifegivessamplesbenefits,
      title={When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs}, 
      author={Ammar Khairi and Daniel D'souza and Ye Shen and Julia Kreutzer and Sara Hooker},
      year={2025},
      eprint={2506.20544},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.20544}, 
}
```

## Disclaimer
The translation into 22 languages is performed with an in-house state-of-the-art translation model.