BlenderRAG: High-Fidelity 3D Object Generation via Retrieval-Augmented Code Synthesis

ArXi:2605.00632v1 Announce Type: cross Automatic generation of executable Blender code from natural language remains challenging, with state-of-the-art LLMs producing frequent syntactic errors and geometrically inconsistent objects. We present BlenderRAG, a retrieval-augmented generation system that operates on a curated multimodal dataset of 500 expert-validated examples (text, code, image) across 50 object categories.