Symbolic rule-based evaluation of 3D scenes is more reliable and interpretable than vision-language model judges, and text-only LLMs can outperform vision models at refining spatial layouts when given explicit constraint feedback.
SceneCritic is a symbolic evaluator that assesses 3D indoor scene layouts by checking semantic, orientation, and geometric consistency against a structured spatial ontology built from real-world scene data.