metadata
license: mit
language:
- en
pretty_name: Molmo2-ER SAT
tags:
- embodied-reasoning
- molmo2
- molmo2-er
- vlm-training-data
Molmo2-ER · array/SAT
Spatial Aptitude Training: 175K binary-MCQ VQA pairs over ProcTHOR indoor scenes.
This is a re-hosted, loader-ready subset of the upstream dataset, used to train allenai/Molmo2-ER-4B. Files mirror the upstream layout; nothing in the data has been modified.
Upstream source
- Original dataset: array/SAT
- Paper: SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models (arXiv:2412.07755)
- License:
mit(inherits from upstream)
If you use this data, please cite the original authors:
@misc{ray2025satdynamicspatialaptitude,
title={SAT: Dynamic Spatial Aptitude Training for Multimodal Language Models},
author={Arijit Ray and Jiafei Duan and Ellis Brown and others},
year={2025},
eprint={2412.07755},
archivePrefix={arXiv}
}
Usage in Molmo2-ER
See the allenai/molmo2 repository for the data loader and training recipe. The relevant loader class for this dataset lives in olmo/data/spatial_datasets.py.