QileXu/PointLLM-R-7B

PointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought

Chaoqi Chen¹*, Qile Xu¹*, Wenjun Zhou¹, Hui Huang¹†

¹Shenzhen University    *Equal contribution    †Corresponding author

Paper | Project Page | Code | Collection

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Official model weights for the paper PointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought (SIGGRAPH 2026).

PointLLM-R-7B is a 3D multimodal LLM fine-tuned from PointLLM on the PoCoTI-55K dataset, which augments point-cloud QA pairs with structured 5-step chain-of-thought reasoning.

Links

• 📄 Paper: https://arxiv.org/abs/2605.22013
• 🌐 Project page: https://vcc.tech/research/2026/PointLLM-R
• 💻 Code: https://github.com/Xqle/PointLLM-R
• 📦 Collection: https://huggingface.co/collections/QileXu/pointllm-r
• 🗂️ Training data: QileXu/PoCoTI-55K
• 📊 Eval GT: QileXu/OmniObject3D_brief_description_val_GT

Quick Start

See the GitHub repository for installation, inference, and evaluation instructions.

Citation

@inproceedings{chen2026pointllmr,
  title     = {PointLLM-R: Enhancing 3D Point Cloud Reasoning via Chain-of-Thought},
  author    = {Chen, Chaoqi and Xu, Qile and Zhou, Wenjun and Huang, Hui},
  booktitle = {ACM SIGGRAPH},
  year      = {2026},
  pages     = {}
}

License

MIT. The base model and Objaverse-derived data retain their original licenses.