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---
license: apache-2.0
dataset_info:
features:
- name: question_id
dtype: string
- name: category
dtype: string
- name: cluster
dtype: string
- name: turns
list:
- name: content
dtype: string
splits:
- name: train
num_bytes: 251691
num_examples: 500
download_size: 154022
dataset_size: 251691
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
## Arena-Hard-Auto
**Arena-Hard-Auto-v0.1** ([See Paper](https://arxiv.org/abs/2406.11939)) is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries sourced from Chatbot Arena. We prompt GPT-4-Turbo as judge to compare the models' responses against a baseline model (default: GPT-4-0314). Notably, Arena-Hard-Auto has the highest *correlation* and *separability* to Chatbot Arena among popular open-ended LLM benchmarks ([See Paper](https://arxiv.org/abs/2406.11939)). If you are curious to see how well your model might perform on Chatbot Arena, we recommend trying Arena-Hard-Auto.
Please checkout our GitHub repo on how to evaluate models using Arena-Hard-Auto and more information about the benchmark.
If you find this dataset useful, feel free to cite us!
```
@article{li2024crowdsourced,
title={From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline},
author={Li, Tianle and Chiang, Wei-Lin and Frick, Evan and Dunlap, Lisa and Wu, Tianhao and Zhu, Banghua and Gonzalez, Joseph E and Stoica, Ion},
journal={arXiv preprint arXiv:2406.11939},
year={2024}
}
```
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