TopoAgent: A Structure-Aware Perception-to-Reasoning Framework for Diagram-to-Graph Topology Extraction with Large Vision-Language Models
Diagram-to-graph topology extraction aims to extract a graph of entities and their connections from a structural diagram. This task remains challenging for current vision-language models because it requires both fine-grained perceptual grounding and topology-aware reasoning with global consistency. We present TopoBench-180, a human-verified benchmark for diagram-to-graph topology extraction, and TopoAgent, a structure-aware perception-to-reasoning framework for reliable topology extraction using large vision-language models. TopoBench-180 contains 180 structural diagrams spanning Web-style and Network-style categories, paired with canonical graph annotations. TopoAgent progressively extra...
| Authors | Bangwei Guo, Xujiang Zhao, Yanchi Liu et al. |
|---|---|
| Primary category | cs.CV |
| Published | 27 August 2026 |
| Last updated at source | 27 August 2026 |
Connected in the knowledge graph
- WayneGuo0011/TopoBench-180Dataset · cited by
- WayneGuo0011/KnossosDataset · cited by
Models and datasets referencing this paper
- WayneGuo0011/KnossosDataset
- WayneGuo0011/TopoBench-180Dataset
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