--- license: cc-by-sa-4.0 task_categories: - visual-question-answering - question-answering tags: - charts - vision-language - chart-question-answering - synthetic-data pretty_name: Chartographer size_categories: - 1K ## Fields Rows are stored in `data/*.jsonl`. - `chart_id`: chart identifier, shared by the original chart, reconstruction, and seed variants of the same chart. - `question_id`: question identifier, shared by all variants for the same question. - `variant`: chart variant, one of `original`, `reconstruction`, or `seed_0` through `seed_9`. - `image`: relative path to the released chart image; empty for `original` rows because upstream original images are not included. - `question`: question asked about the chart image. - `answer`: reference answer for the row's chart variant. - `chart_data`: relative path to the released chart data JSON; empty for `original` rows. - `source_dataset_split`: source dataset split identifier for this Chartographer row, combining the upstream dataset and split used in the release. - `source_row_index`: zero-based row index in the upstream dataset split identified by `source_dataset_split`. ## Intended Use Chartographer is intended for chart visual question answering evaluation, especially comparisons between original charts, reconstructed charts, and controlled counterfactual chart variants. ## License Notes Chartographer is released under CC BY-SA 4.0 where permitted by the source terms. Upstream original images are not included and may be governed by separate licenses. To recover upstream original images and source records, use `source_row_index` with the upstream Hugging Face dataset and split listed in `metadata/dataset_info.json`. Chartographer keeps its own evaluated `question` and `answer` fields, which may differ from the exact QA text stored in the upstream Hugging Face row. ## Citation ```bibtex @misc{jiang2026chartographer, title={Chartographer: Counterfactual Chart Generation for Evaluating Vision-Language Models}, author={Yifan Jiang and Dae Yon Hwang and Jesse C. Cresswell and Freda Shi}, year={2026}, eprint={2605.27311}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2605.27311}, } ``` ## Loading ```python from datasets import load_dataset ds = load_dataset("json", data_files={ "chartmuseum_dev": "data/chartmuseum_dev.jsonl", "chartqa_val": "data/chartqa_val.jsonl", "charxiv_validation": "data/charxiv_validation.jsonl", }) ```