| --- |
| dataset_info: |
| - config_name: de |
| features: |
| - name: image_index |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: graph_type |
| dtype: string |
| - name: source_code |
| dtype: string |
| - name: persona |
| dtype: string |
| - name: question_type |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer_format |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 602502623 |
| num_examples: 19948 |
| download_size: 587343405 |
| dataset_size: 602502623 |
| - config_name: en |
| features: |
| - name: image_index |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: graph_type |
| dtype: string |
| - name: source_code |
| dtype: string |
| - name: persona |
| dtype: string |
| - name: question_type |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer_format |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 3576551306 |
| num_examples: 119920 |
| download_size: 3486996146 |
| dataset_size: 3576551306 |
| - config_name: es |
| features: |
| - name: image_index |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: graph_type |
| dtype: string |
| - name: source_code |
| dtype: string |
| - name: persona |
| dtype: string |
| - name: question_type |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer_format |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 596659078 |
| num_examples: 19994 |
| download_size: 581167827 |
| dataset_size: 596659078 |
| - config_name: fr |
| features: |
| - name: image_index |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: graph_type |
| dtype: string |
| - name: source_code |
| dtype: string |
| - name: persona |
| dtype: string |
| - name: question_type |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer_format |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 585962483 |
| num_examples: 19988 |
| download_size: 569284533 |
| dataset_size: 585962483 |
| - config_name: it |
| features: |
| - name: image_index |
| dtype: int64 |
| - name: image |
| dtype: image |
| - name: graph_type |
| dtype: string |
| - name: source_code |
| dtype: string |
| - name: persona |
| dtype: string |
| - name: question_type |
| dtype: string |
| - name: question |
| dtype: string |
| - name: answer_format |
| dtype: string |
| - name: answer |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 581981329 |
| num_examples: 19962 |
| download_size: 567288829 |
| dataset_size: 581981329 |
| configs: |
| - config_name: de |
| data_files: |
| - split: train |
| path: de/train-* |
| - config_name: en |
| data_files: |
| - split: train |
| path: en/train-* |
| - config_name: es |
| data_files: |
| - split: train |
| path: es/train-* |
| - config_name: fr |
| data_files: |
| - split: train |
| path: fr/train-* |
| - config_name: it |
| data_files: |
| - split: train |
| path: it/train-* |
| license: odc-by |
| task_categories: |
| - visual-question-answering |
| language: |
| - fr |
| - it |
| - de |
| - en |
| - es |
| size_categories: |
| - 100K<n<1M |
| --- |
| |
| ## multi_figureQA |
| |
| ### Overview |
| **Multi-FigureQA** is *visual question-answering (VQA)* and reasoning dataset based on Microsoft's [FigureQA](https://www.microsoft.com/en-us/research/project/figureqa-dataset/) dataset. |
| |
| The original FigureQA dataset consists of synthetic, scientific-style figures (such as dot-line plots, line plots, horizontal and vertical bar graphs and pie charts) paired with source data and Q&A pairs. |
| |
| |
| While the original FigureQA dataset provides clean synthetic data for basic chart comprehension, its plots lack realistic labels, titles, and domain-specific context. As a result, the generated figures offer limited practical utility for contemporary visual reasoning tasks. |
| |
| ##### *For more information about Microsoft's FigureQA VQA dataset check the realated [paper on ArXiv](https://arxiv.org/abs/1710.07300).* |
| |
| --- |
| |
| |
| To overcome the abstract nature of the original dataset, Multi-FigureQA introduces **persona-driven figure generation**. By using detailed persona descriptions, the pipeline generates domain-specific titles, descriptive labels, and realistic data distributions, significantly increasing the dataset's practical utility. |
| Q&A pairs are then generated on the basis of the Persona and related figure. |
| |
| In-prompt instructions ensure question ad topic diversity and strict answer format. |
| - Questions and answers rely exclusively on what is visibly displayed in the chart and described in the source code. |
| - The generation logic restricts questions when chart values are visually too close to differentiate, preventing unanswerable or ambiguous answers. |
| - To prevent over-representation of simple extreme values, questions are evenly distributed across four distinct categories: `highest_lowest`,`pairwise_comparison`, `relative_ranking`, `presence_composition`. |
| - Responses are structured into four constrained formats: `yes_no`,`detailed_explanation`, `concise`, `label_only`. |
|
|
| ### Dataset structure |
| ``` |
| { |
| "image_index": int64, |
| "image": image, |
| "graph_type": string, |
| "source_code": string, |
| "persona": string, |
| "question_type": string |
| "question": string, |
| "answer_format": string |
| "answer": string |
| } |
| ``` |
| ### Multilingual generation |
|
|
| The dataset contains approximately 200,000 samples, with 60% in English. The remaining 40% is distributed evenly among French, Spanish, German, and Italian (10% each). |
| The final distribution is as follows: |
|
|
| | Language | Subset Name | Percentage | Number of Examples | |
| |----------|-------------|------------|--------------------| |
| | English | en | 60% | 119,920 | |
| | Italian | it | 10% | 19,962 | |
| | French | fr |10% | 19,988 | |
| | Spanish | es | 10% | 19,994 | |
| | German | de | 10% | 19,948 | |
| | **Total**| | **100%** | **199,812** | |
|
|
| ### Models |
| Figure and Q&A generation was achieved using the state-of-the-art, permissively licensed model `Qwen/Qwen3.5-122B-A10B-FP8`. |
|
|
| ## Licensing |
| The dataset is distributed under the ODC-BY-1.0 license. Users must adhere to the attribution and usage requirements outlined under this license. |
