Apples on the Table? Evaluating Text-Guided 3D Scene Synthesis via Fine-Grained Constraint Verification

The paper introduces LEGO, a benchmark dataset pairing user text descriptions with human‑annotated fine‑grained constraints and reference 3D scenes, and LEGO‑Eval, an evaluation framework that decomposes descriptions into atomic constraints and verifies each using grounding and spatial reasoning tools. It demonstrates that LEGO‑Eval detects misalignment more accurately than existing methods and that current 3D scene synthesis approaches achieve at most a 10% success rate on this benchmark.

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• agents
• robotics
• benchmarks
• safety