AI RESEARCH
VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing
arXiv CS.CL
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ArXi:2605.15677v1 Announce Type: new Despite the rapid advancements in Vision-Language Models (VLMs), a critical gap remains in their ability to handle structured, controllable diagrammatic tasks essential for professional workflows. Existing methods predominantly rely on pixel-based synthesis, which operates in probabilistic pixel spaces and is inherently limited in editability and fidelity. Instead, we propose a new Diagram-as-Code paradigm with symbolic logic that leverages mxGraph Extensible Markup Language (XML) for precise diagram generation and editing.