Improve dataset card: Update license, size category, task category, and code link

This PR improves the dataset card for OST-Bench by:
- Updating the `license` to the specific `cc-by-nc-4.0` based on the GitHub repository's license information.
- Refining the `size_categories` to `10K<n<100K` to accurately reflect the dataset's 10,000 examples.
- Adding `image-text-to-text` to `task_categories` for better discoverability, complementing the existing specific VQA tasks.
- Fixing a typo in the introductory sentence ("Unstanding" to "Understanding").
- Unifying the "Code" link to `https://github.com/rbler1234/OST-Bench` for consistency with the project's GitHub README and evaluation instructions.

README.md

@@ -1,43 +1,44 @@
 ---
-license: cc
+language:
+- en
+license: cc-by-nc-4.0
+size_categories:
+- 10K<n<100K
 task_categories:
 - question-answering
 - multiple-choice
 - visual-question-answering
-language:
-- en
+- image-text-to-text
 pretty_name: OST-Bench
-size_categories:
-- 1K<n<
 dataset_info:
   features:
-    - name: scan_id
-      dtype: string
-    - name: turn_id
-      dtype: int64
-    - name: type
-      dtype: string
-    - name: new_observations
-      sequence: string
-    - name: origin_question
-      dtype: string
-    - name: option
-      sequence: string
-    - name: answer
-      dtype: string
+  - name: scan_id
+    dtype: string
+  - name: turn_id
+    dtype: int64
+  - name: type
+    dtype: string
+  - name: new_observations
+    sequence: string
+  - name: origin_question
+    dtype: string
+  - name: option
+    sequence: string
+  - name: answer
+    dtype: string
   splits:
-    - name: test
-      num_examples: 10000
+  - name: test
+    num_examples: 10000
 configs:
-  - config_name: default
-    data_files:
-      - split: test
-        path: OST_bench.json
+- config_name: default
+  data_files:
+  - split: test
+    path: OST_bench.json
 ---
 
-This page contains the data for the paper "OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Unstanding." 
+This page contains the data for the paper "OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding." 
 
-[**🌐 Homepage**](https://rbler1234.github.io/OSTBench.github.io/)  | [**📑 Paper**](https://arxiv.org/pdf/2507.07984) | [**💻 Code**](https://github.com/OpenRobotLab/OST-Bench) | [**📖 arXiv**](https://arxiv.org/abs/2507.07984)
+[**🌐 Homepage**](https://rbler1234.github.io/OSTBench.github.io/)  | [**📑 Paper**](https://arxiv.org/pdf/2507.07984) | [**💻 Code**](https://github.com/rbler1234/OST-Bench) | [**📖 arXiv**](https://arxiv.org/abs/2507.07984)
 
 ## Dataset Description
 The `imgs` folder contains image data corresponding to 1,386 scenes. Each scene has its own subfolder, which stores the observations captured by the agent while exploring that scene.
@@ -61,4 +62,4 @@ ost-bench.json consists of 10k data samples, where each sample represents one ro
 Samples with the same `scan_id` belong to the same multi-turn conversation group. During model evaluation, each multi-turn conversation group is processed as a unit: the shared `system_prompt` is provided, and new observations along with questions are fed in sequentially according to `turn_id`.
 
 ## Evaluation Instructions
-Please refer to our  [evaluation code](https://github.com/rbler1234/OST-Bench) for details.
+Please refer to our [evaluation code](https://github.com/rbler1234/OST-Bench) for details.