From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing

Fuente: arXiv
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Autori principali: Wei, Jingxuan, Tan, Cheng, Chen, Qi, Wu, Gaowei, Li, Siyuan, Gao, Zhangyang, Sun, Linzhuang, Yu, Bihui, Guo, Ruifeng
Natura: Preprint
Pubblicazione: 2024
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author Wei, Jingxuan
Tan, Cheng
Chen, Qi
Wu, Gaowei
Li, Siyuan
Gao, Zhangyang
Sun, Linzhuang
Yu, Bihui
Guo, Ruifeng
author_facet Wei, Jingxuan
Tan, Cheng
Chen, Qi
Wu, Gaowei
Li, Siyuan
Gao, Zhangyang
Sun, Linzhuang
Yu, Bihui
Guo, Ruifeng
contents We introduce the task of text-to-diagram generation, which focuses on creating structured visual representations directly from textual descriptions. Existing approaches in text-to-image and text-to-code generation lack the logical organization and flexibility needed to produce accurate, editable diagrams, often resulting in outputs that are either unstructured or difficult to modify. To address this gap, we introduce DiagramGenBenchmark, a comprehensive evaluation framework encompassing eight distinct diagram categories, including flowcharts, model architecture diagrams, and mind maps. Additionally, we present DiagramAgent, an innovative framework with four core modules-Plan Agent, Code Agent, Check Agent, and Diagram-to-Code Agent-designed to facilitate both the generation and refinement of complex diagrams. Our extensive experiments, which combine objective metrics with human evaluations, demonstrate that DiagramAgent significantly outperforms existing baseline models in terms of accuracy, structural coherence, and modifiability. This work not only establishes a foundational benchmark for the text-to-diagram generation task but also introduces a powerful toolset to advance research and applications in this emerging area.
format Preprint
id arxiv_https___arxiv_org_abs_2411_11916
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing
Wei, Jingxuan
Tan, Cheng
Chen, Qi
Wu, Gaowei
Li, Siyuan
Gao, Zhangyang
Sun, Linzhuang
Yu, Bihui
Guo, Ruifeng
Databases
We introduce the task of text-to-diagram generation, which focuses on creating structured visual representations directly from textual descriptions. Existing approaches in text-to-image and text-to-code generation lack the logical organization and flexibility needed to produce accurate, editable diagrams, often resulting in outputs that are either unstructured or difficult to modify. To address this gap, we introduce DiagramGenBenchmark, a comprehensive evaluation framework encompassing eight distinct diagram categories, including flowcharts, model architecture diagrams, and mind maps. Additionally, we present DiagramAgent, an innovative framework with four core modules-Plan Agent, Code Agent, Check Agent, and Diagram-to-Code Agent-designed to facilitate both the generation and refinement of complex diagrams. Our extensive experiments, which combine objective metrics with human evaluations, demonstrate that DiagramAgent significantly outperforms existing baseline models in terms of accuracy, structural coherence, and modifiability. This work not only establishes a foundational benchmark for the text-to-diagram generation task but also introduces a powerful toolset to advance research and applications in this emerging area.
title From Words to Structured Visuals: A Benchmark and Framework for Text-to-Diagram Generation and Editing
topic Databases
url https://arxiv.org/abs/2411.11916