Update README.md

README.md

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 ### GlobalRG - Retrieval Across Universals Task
 Despite recent advancements in vision-language models, their performance remains suboptimal on images from non-western cultures due to underrepresentation in training datasets. Various benchmarks have been proposed to test models' cultural inclusivity, but they have limited coverage of cultures and do not adequately assess cultural diversity across universal as well as culture-specific local concepts. We introduce the GlobalRG-Retrieval benchmark, which aims at retrieving culturally diverse images for universal concepts from 50 countries.
 
-<!-- > **Note:** The answers for the GlobalRG-Grounding benchmark are not publicly available. We are working on creating a competition where participants can upload their predictions and evaluate their models. Stay tuned for more updates!
-If you need to urgently need to evaluate, please contact [email protected] -->
+> **Note:** The answers for the GlobalRG-Retrieval benchmark are not publicly available. We are working on creating a competition where participants can upload their predictions and evaluate their models. Stay tuned for more updates!
+If you need to urgently need to evaluate, please contact [email protected] and fill out this form. https://forms.gle/pSbnGso13co6V4518. 
 
 ### Loading the dataset
 To load and use the GlobalRG-Grounding benchmark, use the following commands: