Link model card to paper (#1)

- Link model card to paper (ab30ae2031aaef1c7114e52494c45d55e207b505)


Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>

README.md

@@ -1,7 +1,11 @@
 ---
-license: apache-2.0
+datasets:
+- custom
 language:
 - en
+library_name: pytorch
+license: apache-2.0
+pipeline_tag: image-feature-extraction
 tags:
 - computer-vision
 - self-supervised-learning
@@ -11,10 +15,6 @@ tags:
 - depth-estimation
 - semantic-segmentation
 - pytorch
-datasets:
-- custom
-library_name: pytorch
-pipeline_tag: image-feature-extraction
 ---
 
 # LingBot-Vision
@@ -44,9 +44,9 @@ Each checkpoint contains backbone weights only. Training-time heads, optimizer s
 
 ### Model Sources
 
+- **Paper:** [Vision Pretraining for Dense Spatial Perception](https://huggingface.co/papers/2607.05247)
 - **Repository:** https://github.com/robbyant/lingbot-vision
 - **Project Page:** https://technology.robbyant.com/lingbot-vision
-- **Technical Report:** coming soon
 
 ### Related Models
 
@@ -136,4 +136,4 @@ The `variant` argument can be `giant`, `large`, `base`, or `small`. You can also
 ## Model Card Contact
 
 - **Issues:** https://github.com/robbyant/lingbot-vision/issues
-- **Email:** fuzelin.fzl@antgroup.com, xuenan.xue@antgroup.com
+- **Email:** fuzelin.fzl@antgroup.com, xuenan.xue@antgroup.com