Improve dataset card: Add task category, paper/code/project links, and sample usage

README.md

@@ -1,15 +1,24 @@
 ---
-license: mit
 language:
 - en
+license: mit
 tags:
 - biology
 - medical
 - point cloud
 - completion
+task_categories:
+- GRAPH_MACHINE_LEARNING
 ---
+
 ### MedPointS-CPL
-This is the medical point cloud completion dataset from [MedPointS](https://flemme-docs.readthedocs.io/en/latest/medpoints.html), where `partial` is the partial point cloud, 'target' is the target point cloud, and `label` is the class label. 
+This is the medical point cloud completion dataset from [MedPointS](https://flemme-docs.readthedocs.io/en/latest/medpoints.html), as presented in the paper "Hierarchical Feature Learning for Medical Point Clouds via State Space Model".
+
+-   **Paper**: [Hierarchical Feature Learning for Medical Point Clouds via State Space Model](https://huggingface.co/papers/2504.13015)
+-   **Code**: https://github.com/wlsdzyzl/flemme
+-   **Project page**: https://flemme-docs.readthedocs.io/en/latest/medpoints.html
+
+In this dataset, `partial` is the partial point cloud, 'target' is the target point cloud, and `label` is the class label.
 
 Each point cloud has been normalized and sub-sampled to 2048 points. The correspondence between class names and labels is listed as follows (the label value plus 1 is the actual key of following map):
 
@@ -68,7 +77,18 @@ coarse_label_to_organ = {1: 'adrenalgland',
     }
 ```
 
-If you find our project helpful, please consider to cite the following works:
+### Sample Usage
+
+To train and evaluate models for point cloud completion using the Flemme framework, you can use the following commands. Note that you may need to adjust `/path/to/project/flemme/` to your local Flemme installation path.
+
+```bash
+## completion
+train_flemme --config /path/to/project/flemme/resources/pcd/medpoints/cpl/train_pointmamba2knn_cpl.yaml
+test_flemme --config /path/to/project/flemme/resources/pcd/medpoints/cpl/test_pointmamba2knn_cpl.yaml
+```
+
+### Citation
+If you find our project helpful, please consider to cite the following work:
 
 ```
 @misc{zhang2025hierarchicalfeaturelearningmedical,
@@ -80,28 +100,4 @@ If you find our project helpful, please consider to cite the following works:
       primaryClass={cs.CV},
       url={https://arxiv.org/abs/2504.13015}, 
 }
-```
-
----
-dataset_info:
-  features:
-  - name: partial
-    sequence:
-      sequence: float32
-  - name: target
-    sequence:
-      sequence: float32
-  - name: label
-    sequence: float32
-  splits:
-  - name: train
-    num_bytes: 1888940484
-    num_examples: 28737
-  download_size: 1438880848
-  dataset_size: 1888940484
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+```