Update paper and add GitHub links to dataset card

README.md

@@ -1,23 +1,26 @@
 ---
-license: apache-2.0
 language:
 - en
-tags:
-- underwater 
-- instance 
-- segmentation
-- image
-- text
+license: apache-2.0
 size_categories:
 - 10K<n<100K
 task_categories:
 - image-segmentation
 - object-detection
 - image-classification
+tags:
+- underwater
+- instance
+- segmentation
+- image
+- text
 ---
- We propose a large-scale underwater instance segmentation dataset, [**UIIS10K**](#datasets), which includes **10,048 images** with pixel-level annotations for 10 categories. As far as we know, this is **the largest underwater instance segmentation dataset** available and can be used as a benchmark for evaluating underwater segmentation methods. 
+
+We propose a large-scale underwater instance segmentation dataset, [**UIIS10K**](#datasets), which includes **10,048 images** with pixel-level annotations for 10 categories. As far as we know, this is **the largest underwater instance segmentation dataset** available and can be used as a benchmark for evaluating underwater segmentation methods. 
  
- More information about this dataset pleaser refer to "[Advancing Marine Research: UWSAM Framework and UIIS10K Dataset for Precise Underwater Instance Segmentation](https://arxiv.org/abs/2505.15581)".
+More information about this dataset please refer to "[Advancing Marine Research: UWSAM Framework and UIIS10K Dataset for Precise Underwater Instance Segmentation](https://huggingface.co/papers/2505.15581)".
+
+Code: https://github.com/LiamLian0727/UIIS10K
  
 The dataset in `UIIS10K.zip` follows the COCO format and is organized as follows:
 ```
@@ -47,7 +50,7 @@ If you find our repo useful for your research, please cite us:
 
 @article{UIIS10K_Dataset_2025,
     author    = {Hua Li, Shijie Lian, Zhiyuan Li, Runmin Cong, Chongyi Li, Laurence T. Yang, Weidong Zhang, Sam Kwong},
-    title     = {Taming SAM for Underwater Instance Segmentation and Beyond},
+    title     = {Advancing Marine Research: UWSAM Framework and UIIS10K Dataset for Precise Underwater Instance Segmentation},
     year      = {2025},
     journal   = {arXiv preprint arXiv:2505.15581},
 }