Enhance dataset card: Add task categories, language, tags, and sample usage

This PR improves the dataset card by:
- Adding `task_categories: ['video-text-to-text']` to the metadata, enabling better discoverability on the Hugging Face Hub under relevant AI tasks.
- Adding `language: ['en']` as the dataset content is in English.
- Including relevant `tags` such as `autonomous-driving`, `nuscenes`, `temporal-reasoning`, `video-question-answering`, and `vlm` for more detailed categorization.
- Adding a "Sample Usage" section with a Python code snippet directly from the GitHub README, making it easier for users to get started with the dataset. This section also includes important setup information for loading the benchmark splits.

README.md

@@ -1,5 +1,15 @@
 ---
 license: cc-by-nc-sa-4.0
+task_categories:
+- video-text-to-text
+language:
+- en
+tags:
+- autonomous-driving
+- nuscenes
+- temporal-reasoning
+- video-question-answering
+- vlm
 configs:
 - config_name: action_duration
   data_files:
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-    - name: ffea14e6b78649839de381f51f4f665f
-      list: string
-    - name: fff7106ca1f34c7a83e72ffbc0c0b1b5
-      list: string
+
   - name: keyframes_token_formatted
     list:
     - name: frames
@@ -3283,6 +2348,7 @@ dataset_info:
   download_size: 10228
   dataset_size: 37059
 ---
+
 <div align="center">
   <h1>Dataset for "From Segments to Scenes: Temporal Understanding in Autonomous Driving via Vision-Language Models"</h1>
 <a href="https://arxiv.org/abs/2512.05277" target="_blank">
@@ -3302,6 +2368,27 @@ dataset_info:
   <img src="./figs/teaser_sub1.png" alt="Figure 1" width=90%"/>
 </p>
 
+## Sample Usage
+
+You can download the benchmark using the following Python code snippet.
+```python
+from datasets import load_dataset 
+
+# --- Load a specific subset by name --- 
+action_duration = load_dataset("vbdai/TAD", name="action_duration") 
+exact_answer_action = load_dataset("vbdai/TAD", name="exact_answer_action") 
+mc_action = load_dataset("vbdai/TAD", name="mc_action") 
+relative_action_localize = load_dataset("vbdai/TAD", name="relative_action_localize") 
+temp_action_localize = load_dataset("vbdai/TAD", name="temp_action_localize") 
+temp_object_localize = load_dataset("vbdai/TAD", name="temp_object_localize") 
+temp_ordering = load_dataset("vbdai/TAD", name="temp_ordering") 
+keysegments = load_dataset("vbdai/TAD", name="keysegments") 
+raw_labels = load_dataset("vbdai/TAD", name="raw_labels") 
+print("
+Successfully loaded TAD benchmark from HF Hub")
+```
+Then insert the path of the `.cache` folder including the benchmark splits (e.g. `C:\user\.cache\huggingface\datasets\vbdai___tad\`) into `$BENCHMARK_PATH` in the shell files discussed in the following sections (Shell Scripts).
+
 # Dataset Structure
 
 TAD-Bench is an autonomous driving QA benchmark that consists of seven tasks (or question types). There is a folder in the dataset that corresponds to each of these seven tasks as follows:
@@ -3392,6 +2479,4 @@ This work is licensed under a
 
 [cc-by-nc-sa]: https://creativecommons.org/licenses/by-nc-sa/4.0/
 [cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
-[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg
-
-
+[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg