Datasets:
license: apache-2.0
configs:
- config_name: '2022'
data_files: 2022.jsonl
- config_name: '2023'
data_files: 2023.jsonl
default: true
dataset_info:
features:
- name: id
dtype: string
- name: exam
dtype: string
- name: IU
dtype: bool
- name: ledor
dtype: bool
- name: question
dtype: string
- name: alternatives
sequence: string
- name: figures
sequence: string
- name: description
sequence: string
- name: label
dtype: string
task_categories:
- visual-question-answering
- multiple-choice
language:
- pt
pretty_name: ENEM
size_categories:
- n<1K
The enem 2022 and enem 2023 datasets encompass all multiple-choice questions from the last two editions of the Exame Nacional do Ensino Médio (ENEM), the main standardized entrance examination adopted by Brazilian universities. The datasets have been created to allow the evaluation of both textual-only and textual-visual language models. To evaluate textual-only models, we incorporated into the datasets the textual descriptions of the images that appear in the questions' statements from the orange ENEM exam booklet, a particular booklet that offers accessibility to people with visual impairments.
A repository containing the essential code for utilizing this dataset is accessible here.
If you use this dataset in your research, please acknowledge the papers below by citing them:
@misc{pires2023evaluating,
title={Evaluating GPT-4's Vision Capabilities on Brazilian University Admission Exams},
author={Ramon Pires and Thales Sales Almeida and Hugo Abonizio and Rodrigo Nogueira},
year={2023},
eprint={2311.14169},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
@misc{nunes2023evaluating,
title={Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission Exams},
author={Desnes Nunes and Ricardo Primi and Ramon Pires and Roberto Lotufo and Rodrigo Nogueira},
year={2023},
eprint={2303.17003},
archivePrefix={arXiv},
primaryClass={cs.CL}
}