Update README.md

README.md

@@ -27,7 +27,7 @@ task_categories:
 
 DeepSea MOT consists of 4 video sequences (2 midwater, 2 benthic) with a total of 2,400 frames and 57,376 annotated objects comprising 188 tracks. The videos were captured by the [Monterey Bay Aquarium Research Institute (MBARI)](https://www.mbari.org/) using remotely operated vehicles (ROVs) [*Doc Ricketts*](https://www.mbari.org/technology/rov-doc-ricketts/) and [*Ventana*](https://www.mbari.org/technology/rov-ventana/) in deep-sea environments, showcasing a variety of marine species and underwater scenes.
 
-- **Paper:** https://arxiv.org/abs/TBD
+- **Paper:** https://arxiv.org/abs/2509.03499
 - **Workflow:** https://docs.mbari.org/benchmark_eval/
 
 ## File Structure
@@ -82,7 +82,7 @@ Each sequence directory contains:
 
 ### Dataset Curators
 
-Authors of [[1]](https://arxiv.org/abs/TBD):
+Authors of [[1]](https://arxiv.org/abs/2509.03499):
 
 - Kevin Barnard
 - Elaine Liu
@@ -98,7 +98,7 @@ Authors of [[1]](https://arxiv.org/abs/TBD):
     author = {Barnard, Kevin and Liu, Elaine and Walz, Kristine and Schlining, Brian and Stout, Nancy Jacobsen and Lundsten, Lonny},
     title = { {DeepSea MOT}: A benchmark dataset for multi-object tracking on deep-sea video},
     year = {2025},
-    journal = {arXiv preprint arXiv:2501.XXXXX},
-    doi = {10.48550/arXiv.2501.XXXXX},
+    journal = {arXiv preprint arXiv:2509.03499)},
+    doi = {10.48550/arXiv.2509.03499},
 }
 ```