Datasets:
File size: 1,883 Bytes
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license: apache-2.0
language:
- en
pretty_name: Molmo2-ER RefSpatial
tags:
- embodied-reasoning
- molmo2
- molmo2-er
- vlm-training-data
---
# Molmo2-ER · JingkunAn/RefSpatial
2.5M spatial-referring corpus (web + indoor + simulated) covering 31 spatial relations.
This is a re-hosted, **loader-ready subset** of the upstream dataset, used to train [`allenai/Molmo2-ER-4B`](https://huggingface.co/allenai/Molmo2-ER-4B). Files mirror the upstream layout; nothing in the data has been modified.
## Upstream source
- **Original dataset:** [JingkunAn/RefSpatial](https://huggingface.co/datasets/JingkunAn/RefSpatial)
- **Paper:** *RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics* ([arXiv:2506.04308](https://arxiv.org/abs/2506.04308))
- **License:** `apache-2.0` (inherits from upstream)
If you use this data, please cite the original authors:
```bibtex
@misc{zhou2026roboreferspatialreferringreasoning,
title={RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics},
author={Enshen Zhou and Jingkun An and Cheng Chi and others},
year={2026},
eprint={2506.04308},
archivePrefix={arXiv}
}
```
## Extracting before training
This release ships archives. Extract them in-place before pointing `SPATIAL_DATA_HOME` at this directory:
```bash
# Reassemble multipart archives, then extract
cat 2D/depth/depth.tar.gz.part_* > 2D/depth/depth.tar.gz
cat 2D/image/image.tar.gz.part_* > 2D/image/image.tar.gz
cat 3D/image_visual_choice/image_visual_choice.tar.gz.part_* > 3D/image_visual_choice/image_visual_choice.tar.gz
find . -name '*.tar.gz' -execdir tar -xzf {} \;
```
## Usage in Molmo2-ER
See the [`allenai/molmo2`](https://github.com/allenai/molmo2) repository for the data loader and training recipe. The relevant loader class for this dataset lives in `olmo/data/spatial_datasets.py`.
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