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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.
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