Improve model card: add metadata and link paper

Hi! I'm Niels from the Hugging Face community science team.

This PR improves the documentation for this model:
- Adds `pipeline_tag: image-segmentation` to the metadata for better discoverability.
- Links the repository to its associated research paper on Hugging Face Papers.
- Adds a brief summary of the model and its results based on the paper and GitHub README.

Feel free to merge if this looks good to you!

README.md

@@ -1,10 +1,33 @@
 ---
 license: mit
+pipeline_tag: image-segmentation
 ---
+
 # LaSSM: Efficient Semantic-Spatial Query Decoding via Local Aggregation and State Space Models for 3D Instance Segmentation
-[[code]](https://github.com/RayYoh/LaSSM)
+
+This repository contains the weights for **LaSSM**, a framework for efficient 3D scene instance segmentation from point clouds.
+
+- **Paper:** [LaSSM: Efficient Semantic-Spatial Query Decoding via Local Aggregation and State Space Models for 3D Instance Segmentation](https://huggingface.co/papers/2602.11007)
+- **Code:** [GitHub - RayYoh/LaSSM](https://github.com/RayYoh/LaSSM)
+
+## Description
+LaSSM (Local Aggregation and State Space Models) prioritizes simplicity and efficiency in 3D instance segmentation. It introduces a hierarchical semantic-spatial query initializer and a coordinate-guided state space model (SSM) decoder. This design restricts the model to focus on geometrically coherent regions and uses a spatial dual-path SSM block to capture underlying dependencies within the query set, reducing redundant computation.
+
+LaSSM ranks first on the ScanNet++ V2 leaderboard, outperforming previous state-of-the-art methods with significantly fewer FLOPs.
+
+## Trained Results
 | Model | Benchmark | Num GPUs | mAP | AP50 | AP25 | Config | Tensorboard | Exp Record | Model |
 | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
 | LaSSM | ScanNet++ V2 Val | 4 | 29.1 | 43.5 | 51.6 | [Link](https://github.com/RayYoh/LaSSM/blob/main/configs/scannetpp/insseg-lassm-spunet-v2-3.py) | [Link](https://huggingface.co/RayYoh/LaSSM/tensorboard) | [Link](https://huggingface.co/RayYoh/LaSSM/raw/main/scannetpp-lassm-spunet-v2-3/train.log) | [Link](https://huggingface.co/RayYoh/LaSSM/blob/main/scannetpp-lassm-spunet-v2-3/model/model_best.pth) |
 | LaSSM | ScanNet Val | 4 | 58.4 | 78.1 | 86.1 | [Link](https://github.com/RayYoh/LaSSM/blob/main/configs/scannet/insseg-lassm-spunet-v2-3.py) | - | [Link](https://huggingface.co/RayYoh/LaSSM/raw/main/scannet-lassm-spunet-v2-3/train.log) | [Link](https://huggingface.co/RayYoh/LaSSM/blob/main/scannet-lassm-spunet-v2-3/model/model_best.pth) |
 | LaSSM | ScanNet200 Val | 4 | 29.3 | 39.2 | 44.5 | [Link](https://github.com/RayYoh/LaSSM/blob/main/configs/scannet200/insseg-lassm-minkunet-3.py) | - | [Link](https://huggingface.co/RayYoh/LaSSM/raw/main/scannet200-lassm-minkunet-3/train.log) | [Link](https://huggingface.co/RayYoh/LaSSM/blob/main/scannet200-lassm-minkunet-3/model/model_best.pth) |
+
+## Citation
+```bibtex
+@article{yao2025lassm,
+  title={LaSSM: Efficient Semantic-Spatial Query Decoding via Local Aggregation and State Space Models for 3D Instance Segmentation},
+  author={Yao, Lei and Wang, Yi and Yawen, Cui and Liu, Moyun and Chau, Lap-Pui},
+  journal={arXiv preprint arXiv:2602.11007},
+  year={2025}
+}
+```