Datasets:
metadata
dataset_info:
config_name: full_agreement
features:
- name: ID
dtype: string
- name: Dataset
dtype: string
- name: Set
dtype: string
- name: DatasetsSplit
dtype: string
- name: Language
dtype: string
- name: Prompt
dtype: string
- name: RatingLabel
dtype: string
- name: Response
dtype: string
- name: TasksNamesFull
dtype: string
- name: TaskType
dtype: string
- name: facsco_grm_scaled
dtype: float64
- name: FullPrompt
dtype: string
splits:
- name: train
num_bytes: 10827210
num_examples: 16948
- name: val
num_bytes: 1403770
num_examples: 2180
- name: test
num_bytes: 1255708
num_examples: 2004
- name: heldout_item
num_bytes: 924431
num_examples: 1940
- name: heldout_task
num_bytes: 54887
num_examples: 187
download_size: 1334938
dataset_size: 14466006
configs:
- config_name: full_agreement
data_files:
- split: train
path: full_agreement/train-*
- split: val
path: full_agreement/val-*
- split: test
path: full_agreement/test-*
- split: heldout_item
path: full_agreement/heldout_item-*
- split: heldout_task
path: full_agreement/heldout_task-*
license: mit
language:
- en
Multi-task Creativity Evaluation Dataset (MuCE)
This dataset is introduced in the Creative Preference Optimization and contains human responses and ratings for multiple creativity assessments.
Dataset Sources
See Creative Preference Optimization for a list of sources.
Citation
@misc{ismayilzada2025creativepreferenceoptimization,
title={Creative Preference Optimization},
author={Mete Ismayilzada and Antonio Laverghetta Jr. and Simone A. Luchini and Reet Patel and Antoine Bosselut and Lonneke van der Plas and Roger E. Beaty},
year={2025},
eprint={2505.14442},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2505.14442},
}