| --- |
| license: apache-2.0 |
| task_categories: |
| - text2text-generation |
| - visual-question-answering |
| - image-to-text |
| language: |
| - en |
| configs: |
| - config_name: DiagramCoding |
| data_files: |
| - split: test |
| path: DiagramCoding.json |
| - config_name: DiagramEditing |
| data_files: |
| - split: test |
| path: DiagramEditing.json |
| - config_name: DiagramGeneration |
| data_files: |
| - split: test |
| path: DiagramGeneration.json |
| |
| --- |
| |
|
|
| [📑paper link](https://arxiv.org/abs/2411.11916) |
|
|
| ## Dataset Card: DiagramAgent/DiagramGenBenchmark |
|
|
| ### 1. Overview |
| **DiagramAgent/DiagramGenBenchmark** is a comprehensive benchmark designed for evaluating text-to-diagram generation and editing tasks. It provides a diverse set of diagram types alongside corresponding textual descriptions and code representations, aiming to facilitate research in generating structured visual content from natural language inputs. |
|
|
| ### 2. Dataset Description |
| - **Objective**: |
| To transform textual instructions into structured, logically coherent diagrams. |
| - **Content**: |
| The dataset includes a wide range of diagram types: |
| - **Model Architecture Diagrams** |
| - **Flowcharts** |
| - **Line Charts** |
| - **Directed Graphs** |
| - **Undirected Graphs** |
| - **Tables** |
| - **Bar Charts** |
| - **Mind Maps** |
|
|
| - **Data Format**: |
| Each sample typically contains: |
| - A user instruction or query describing the diagram. |
| - The corresponding diagram code (written primarily in LaTeX or DOT) that can be compiled into a visual diagram. |
|
|
| ### 3. Data Sources |
| - The dataset aggregates samples from multiple public resources: |
| - HuggingFace’s VGQA dataset |
| - Datikz and Datikz-v2 datasets |
| - Open-source repositories on GitHub and Overleaf |
| - **Licensing**: |
| The sources are licensed under CC BY 4.0 or MIT, ensuring open access while respecting original content rights. |
|
|
| ### 4. Citation |
|
|
| If you find our work helpful, feel free to give us a cite. |
|
|
|
|
| ``` |
| @inproceedings{wei2024wordsstructuredvisualsbenchmark, |
| title={From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing}, |
| author={Jingxuan Wei and Cheng Tan and Qi Chen and Gaowei Wu and Siyuan Li and Zhangyang Gao and Linzhuang Sun and Bihui Yu and Ruifeng Guo}, |
| booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, |
| year={2025} |
| } |
| ``` |
