---
language:
- en
license: mit
size_categories:
- n<1K
task_categories:
- text-generation
dataset_info:
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    dtype: string
  - name: metadata
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    - name: triple1_labels
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    num_bytes: 446990
    num_examples: 931
  download_size: 197414
  dataset_size: 446990
configs:
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  data_files:
  - split: train
    path: data/train-*
---

# CREATE: Testing LLMs for Associative Creativity

[**Project Page**](https://manyawadhwa.github.io/projects/create/) | [**Github**](https://github.com/ManyaWadhwa/CREATE) | [**Paper**](https://huggingface.co/papers/2603.09970)

CREATE is a benchmark designed to evaluate models' capacity for creative associative reasoning: the ability to draw novel yet meaningful connections between concepts. It requires models to generate sets of paths connecting concepts in their parametric knowledge. Paths are evaluated based on specificity (distinctiveness and closeness of the connection) and diversity.

## Sample Usage

You can load the benchmark questions using the `datasets` library:

```python
from datasets import load_dataset

data = load_dataset('wadhma/CREATE')['train'].to_pandas() 
print(data['query']) ## the benchmark questions
```

## Citation

```bibtex
@InProceedings{Wadhwa-Et-Al-2026:CREATE,
  title = {CREATE: Testing LLMs for Associative Creativity},
  author = {Manya Wadhwa and Tiasa Singha Roy and Harvey Lederman and Junyi Jessy Li and Greg Durrett},
  booktitle = {arXiv},
  year = {2026},
}
```