Update README.md

README.md

@@ -50,4 +50,6 @@ These enhancements enable VPP-LLaVA to achieve state-of-the-art performance in v
 
 ## Zero-Shot Performance on Unseen Dataset (GSeval)
 
-VPP-LLaVA demonstrates remarkable zero-shot performance on unseen datasets, particularly in challenging scenarios involving part-object and multi-object situations. This capability is crucial for real-world applications where the model may encounter previously unseen objects or complex scenes. The model's ability to generalize and accurately ground visual references in these scenarios highlights its robustness and adaptability.
+VPP-LLaVA demonstrates remarkable zero-shot performance on unseen datasets, particularly in challenging scenarios involving part-object and multi-object situations. This capability is crucial for real-world applications where the model may encounter previously unseen objects or complex scenes. The model's ability to generalize and accurately ground visual references in these scenarios highlights its robustness and adaptability.
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+VPP-LLaVA paper link: https://arxiv.org/abs/2503.15426