Presence Is Not Faithfulness: Figurative Vehicle Intrusion in Text-to-Image Generation

Text-to-image (TTI) models increasingly generate high-quality images from natural-language prompts, yet figurative language exposes a failure: a vehicle that should guide the depiction of a tenor may instead be rendered as a visible object. We call this failure **Figurative Vehicle Intrusion**: the intruding content is textually licensed, but it is assigned the wrong visual role, showing that visual presence is not always faithfulness and that presence-oriented evaluation can miss such errors. To study it systematically, we introduce **V**ehicle **I**ntrusion and **S**emantic **T**enor **A**ssessment (**VISTA**), a multilingual benchmark of figurative prompts organized by Figurative Form and Mapping Mechanism. We further propose **V-Score**, a diagnostic question-answering metric that evaluates role-aware figurative faithfulness in generated images. Evaluations on recent high-performing TTI models show that vehicle intrusion persists across languages and figurative categories. As a lightweight mitigation, we introduce **VISTA-Guard**, which partially reduces vehicle intrusion and suggests a practical path toward more figuratively faithful TTI generation. All resources will be released publicly.