{"ID":2840739,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.13647","arxiv_id":"2511.13647","title":"Part-X-MLLM: Part-aware 3D Multimodal Large Language Model","abstract":"We introduce Part-X-MLLM, a native 3D multimodal large language model that unifies diverse 3D tasks by formulating them as programs in a structured, executable grammar. Given an RGB point cloud and a natural language prompt, our model autoregressively generates a single, coherent token sequence encoding part-level bounding boxes, semantic descriptions, and edit commands. This structured output serves as a versatile interface to drive downstream geometry-aware modules for part-based generation and editing. By decoupling the symbolic planning from the geometric synthesis, our approach allows any compatible geometry engine to be controlled through a single, language-native frontend. We pre-train a dual-encoder architecture to disentangle structure from semantics and instruction-tune the model on a large-scale, part-centric dataset. Experiments demonstrate that our model excels at producing high-quality, structured plans, enabling state-of-the-art performance in grounded Q\\\u0026A, compositional generation, and localized editing through one unified interface. Project page: https://chunshi.wang/Part-X-MLLM/","short_abstract":"We introduce Part-X-MLLM, a native 3D multimodal large language model that unifies diverse 3D tasks by formulating them as programs in a structured, executable grammar. Given an RGB point cloud and a natural language prompt, our model autoregressively generates a single, coherent token sequence encoding part-level boun...","url_abs":"https://arxiv.org/abs/2511.13647","url_pdf":"https://arxiv.org/pdf/2511.13647v1","authors":"[\"Chunshi Wang\",\"Junliang Ye\",\"Yunhan Yang\",\"Yang Li\",\"Zizhuo Lin\",\"Jun Zhu\",\"Zhuo Chen\",\"Yawei Luo\",\"Chunchao Guo\"]","published":"2025-11-17T17:59:52Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[\"Large Language Model\",\"Language Model\"]","project_urls":"[\"https://chunshi.wang/Part-X-MLLM/\"]","has_code":false}