| ---
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| library_name: datasets
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| language:
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| - en
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| tags:
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| - multimodal
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| - reasoning
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| task_categories:
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| - visual-question-answering
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| size_categories:
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| - n<1K
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| configs:
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| - config_name: default
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| data_files:
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| - split: train
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| path: dev120.parquet
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| ---
|
|
|
| # CoWorld-Reasoner-Dev
|
|
|
| [](https://arxiv.org/abs/2610.21910)
|
| [](https://huggingface.co/papers/2610.21910)
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| [](https://github.com/ModalityDance/CoWorld-Reasoner)
|
| [](https://modalitydance.github.io/CoWorld-Reasoner/)
|
|
|
| ## Overview
|
|
|
| **CoWorld-Reasoner-Dev** contains the **120 development examples** used for harness co-evolution in CoWorld Reasoner, with **244 images**:
|
|
|
| - **MMSI-Bench**: 30 examples
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| - **SpinBench**: 30 examples
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| - **CausalSpatial**: 30 examples
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| - **PerceptionBench**: 30 examples
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|
|
| These examples are excluded from the corresponding benchmark evaluations. The `train` split contains the development data, not the evaluation sets.
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|
|
| ## Data Fields
|
|
|
| Each example contains:
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|
|
| - `sample_id`: the example identifier.
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| - `benchmark`: the source benchmark.
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| - `task_type`: the task category.
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| - `answer_type`: the answer format.
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| - `question`: the question, including options when present.
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| - `options`: structured options when available.
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| - `images`: an ordered list of images embedded in the Parquet file.
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| - `image_paths`: the corresponding relative paths used by the code.
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| - `answer`: the reference answer.
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| - `score_spec`: the scoring method.
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|
|
| ## Quick Start
|
|
|
| ### Load the dataset
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|
|
| ```python
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| from datasets import load_dataset
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|
|
| ds = load_dataset("ModalityDance/CoWorld-Reasoner-Dev", split="train")
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| example = ds[0]
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|
|
| print(example["question"])
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| print(example["answer"])
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| print("Number of images:", len(example["images"]))
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| example["images"][0].show()
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| ```
|
|
|
| ### Use with CoWorld Reasoner
|
|
|
| After installing the [code repository](https://github.com/ModalityDance/CoWorld-Reasoner#installation), run:
|
|
|
| ```shell
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| python scripts/prepare/download.py
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| ```
|
|
|
| This saves questions and images to `data/dev120/` and reference answers to `scorer_bundle/data/dev120_evaluator_only.jsonl`.
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|
|
| ## Acknowledgements
|
|
|
| The examples are drawn from [MMSI-Bench](https://arxiv.org/abs/2505.23764v3), [SpinBench](https://arxiv.org/abs/2509.25390), [CausalSpatial](https://arxiv.org/abs/2601.13304), and [PerceptionBench](https://arxiv.org/abs/2607.24957). The source datasets retain their original licenses.
|
|
|
| ## Citation
|
|
|
| Please cite our paper as:
|
|
|
| ```bibtex
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| @misc{cheng2026coworldreasoner,
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| title = {CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness},
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| author = {Dongjie Cheng and Ruifeng Yuan and Ran Wei and Ning Song and Yongqi Li and Wenjie Li},
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| year = {2026},
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| eprint = {2610.21910},
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| archivePrefix = {arXiv},
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| primaryClass = {cs.AI},
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| url = {https://arxiv.org/abs/2610.21910}
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| }
|
| ```
|
|
|
