Update README.md

README.md

@@ -33,4 +33,32 @@ configs:
     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." 
+
+[**🌐 Homepage**](https://rbler1234.github.io/ost-bench.github.io/)  | [**📑 Paper**](https://arxiv.org/pdf/2505.23764) | [**💻 Code**](https://github.com/rbler1234/OST-Bench) | [**📖 arXiv**](https://arxiv.org/abs/2505.23764)
+
+##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.
+
+ost-bench.json consists of 10k data samples, where each sample represents one round of Q&A (question and answer) and includes the new observations for that round. The structure of each sample (dictionary) is as follows:
+
+```python
+{
+  "scan_id" (str): Unique identifier for the scene scan,  
+  "system_prompt" (str): Shared context/prompt for the multi-turn conversation,  
+  "turn_id" (int): Index of the current turn in the dialogue,  
+  "type" (str): Question subtype/category,  
+  "origin_question" (str): Original question text,  
+  "answer" (str): Ground-truth answer,  
+  "option" (list[str]): Multiple-choice options,
+  "new_observations" (list[str]): Relative paths to new observation images (within `imgs` dir),  
+  "user_message" (str): Formatted input prompt for the model,  
+}
+```
+
+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.