Datasets:
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README.md
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---
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license: cc
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task_categories:
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- question-answering
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- multiple-choice
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- visual-question-answering
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language:
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- en
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pretty_name: OST-Bench
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size_categories:
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dataset_info:
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features:
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splits:
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configs:
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---
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This page contains the data for the paper "OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene
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[**π Homepage**](https://rbler1234.github.io/OSTBench.github.io/) | [**π Paper**](https://arxiv.org/pdf/2507.07984) | [**π» Code**](https://github.com/OpenRobotLab/OST-Bench) | [**π arXiv**](https://arxiv.org/abs/2507.07984)
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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`.
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## Evaluation Instructions
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Please refer to our [evaluation code](https://github.com/
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---
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license: cc-by-nc-4.0
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task_categories:
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- question-answering
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- multiple-choice
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- visual-question-answering
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- image-text-to-text
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language:
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- en
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pretty_name: OST-Bench
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size_categories:
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- 10K<n<100K
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dataset_info:
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features:
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- name: scan_id
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dtype: string
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- name: turn_id
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dtype: int64
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- name: type
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dtype: string
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- name: new_observations
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sequence: string
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- name: origin_question
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dtype: string
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- name: option
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sequence: string
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- name: answer
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dtype: string
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splits:
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- name: test
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num_examples: 10000
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configs:
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- config_name: default
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data_files:
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- split: test
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path: OST_bench.json
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---
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This page contains the data for the paper "OST-Bench: Evaluating the Capabilities of MLLMs in Online Spatio-temporal Scene Understanding."
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[**π Homepage**](https://rbler1234.github.io/OSTBench.github.io/) | [**π Paper**](https://arxiv.org/pdf/2507.07984) | [**π» Code**](https://github.com/OpenRobotLab/OST-Bench) | [**π arXiv**](https://arxiv.org/abs/2507.07984)
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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`.
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## Evaluation Instructions
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Please refer to our [evaluation code](https://github.com/OpenRobotLab/OST-Bench) for details.
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