Update README.md

README.md

@@ -82,11 +82,11 @@ language:
 </div>
  -->
 
-📍 Data Availability: The dataset will be publicly released under the CC BY-NC-SA 4.0 license upon official acceptance of the associated paper.
-
-📍 Stay tuned for updates — the Hugging Face repository will be updated with download links and detailed documentation once the paper is accepted.
+<!-- 📍 Data Availability: The dataset will be publicly released under the CC BY-NC-SA 4.0 license upon official acceptance of the associated paper.
 
+<!-- 📍 Stay tuned for updates — the Hugging Face repository will be updated with download links and detailed documentation once the paper is accepted. -->
 
+ -->
 ## Abstract
 
 PaveBench is a large-scale benchmark for pavement distress perception and interactive vision-language analysis on real-world highway inspection images. It supports four core tasks: classification, object detection, semantic segmentation, and vision-language question answering. On the visual side, PaveBench provides large-scale annotations on real top-down pavement images and includes a curated hard-distractor subset for robustness evaluation. On the multimodal side, it introduces PaveVQA, a real-image question answering dataset supporting single-turn, multi-turn, and expert-corrected interactions, covering recognition, localization, quantitative estimation, and maintenance reasoning.