metadata
task_categories:
- image-text-to-text
tags:
- chart-qa
- visual-grounding
CCQA: Curriculum Chart Question Answering
CCQA (Curriculum Chart Question Answering) is a three-level curriculum dataset introduced in the paper CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning.
- Paper: CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning
- Project Page: https://xhguo7.github.io/CURV/
- Repository: https://github.com/xhguo7/CURV
Dataset Summary
CCQA is generated entirely from templates, with no model in the loop. Every question, reasoning step, grounding box, and answer is computed deterministically from plotting data, guaranteeing ground-truth correctness at scale. The curriculum systematically progresses from basic single-operation reasoning to complex multi-chart compositional tasks.
Citation
@article{guo2026curv,
title={CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning},
author={Guo, Xuehang and Zhang, Pingyue and Zhang, Ruiyi and Wang, Zhenhailong and Lyu, Hanrui and Ji, Heng and Sun, Tong and Wang, Qingyun and Li, Manling},
journal={arXiv preprint arXiv:2608.02833},
year={2026}
}