Datasets:
license: cc-by-nc-4.0
task_categories:
- question-answering
- multiple-choice
- visual-question-answering
- image-text-to-text
language:
- en
pretty_name: OST-Bench
size_categories:
- 10K<n<100K
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
splits:
- name: test
num_examples: 10000
configs:
- 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 Understanding."
🌐 Homepage | 📑 Paper | 💻 Code | 📖 arXiv
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:
{
"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 for details.