---
license: mit
library_name: pytorch
tags:
  - pointllm
  - point-cloud
  - 3d
  - multimodal
  - chain-of-thought
  - reasoning
base_model: RunsenXu/PointLLM_7B_v1.2
datasets:
  - QileXu/PoCoTI-55K
language:
  - en
---

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

**Chaoqi Chen**¹\*, **Qile Xu**¹\*, **Wenjun Zhou**¹, **Hui Huang**¹†

¹Shenzhen University    \*Equal contribution    †Corresponding author

[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)

---

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](https://github.com/OpenRobotLab/PointLLM) on the [PoCoTI-55K](https://huggingface.co/datasets/QileXu/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](https://huggingface.co/datasets/QileXu/PoCoTI-55K)
- 📊 Eval GT: [QileXu/OmniObject3D_brief_description_val_GT](https://huggingface.co/datasets/QileXu/OmniObject3D_brief_description_val_GT)

## Quick Start

See the [GitHub repository](https://github.com/Xqle/PointLLM-R) for installation, inference, and evaluation instructions.

## Citation

```bibtex
@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.