allenai/Molmo2-ER-VSI-590K

Molmo2-ER · nyu-visionx/VSI-590K

590K spatial QA samples (image+video) propagated from 3D ground truth and CV pseudo-labels.

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: nyu-visionx/VSI-590K
• Paper: Cambrian-S: Towards Spatial Supersensing in Video (arXiv:2511.04670)
• License: apache-2.0 (inherits from upstream)

If you use this data, please cite the original authors:

@misc{yang2025cambriansspatialsupersensingvideo,
  title={Cambrian-S: Towards Spatial Supersensing in Video},
  author={Shusheng Yang and Jihan Yang and Pinzhi Huang and others},
  year={2025},
  eprint={2511.04670},
  archivePrefix={arXiv}
}

Extracting before training

This release ships archives. Extract them in-place before pointing SPATIAL_DATA_HOME at this directory:

for f in *.tar.gz; do tar -xzf $f; done

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.