Update README.md

README.md

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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-7B
+
+**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** (ACM 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.