Improve dataset card: Add links and correct task category

README.md

@@ -1,13 +1,16 @@
 ---
+language:
+- en
 license: mit
-extra_gated_prompt: >-
-  You agree to not use the dataset to conduct experiments that cause harm to
-  human subjects. Please note that the data in this dataset may be subject to
-  other agreements. Before using the data, be sure to read the relevant
-  agreements carefully to ensure compliant use. Video copyrights belong to the
-  original video creators or platforms and are for academic research use only.
+size_categories:
+- 1K<n<10K
 task_categories:
-- visual-question-answering
+- video-classification
+extra_gated_prompt: You agree to not use the dataset to conduct experiments that cause
+  harm to human subjects. Please note that the data in this dataset may be subject
+  to other agreements. Before using the data, be sure to read the relevant agreements
+  carefully to ensure compliant use. Video copyrights belong to the original video
+  creators or platforms and are for academic research use only.
 extra_gated_fields:
   Name: text
   Company/Organization: text
@@ -55,13 +58,12 @@ configs:
   data_files: json/moving_attribute.json
 - config_name: egocentric_navigation
   data_files: json/egocentric_navigation.json
-language:
-- en
-size_categories:
-- 1K<n<10K
 ---
+
 # MVTamperBench Dataset
 
+[Paper](https://arxiv.org/abs/2412.19794) | [Code](https://github.com/Srikant86/MVTamperBench)
+
 ## Overview
 
 **MVTamperBenchEnd** is a robust benchmark designed to evaluate Vision-Language Models (VLMs) against adversarial video tampering effects. It leverages the diverse and well-structured MVBench dataset, systematically augmented with four distinct tampering techniques:
@@ -177,4 +179,4 @@ If you use MVTamperBench in your research, please cite:
 
 ## License
 
-MVTamperBench is released under the MIT License. See `LICENSE` for details.
+MVTamperBench is released under the MIT License. See `LICENSE` for details.