stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation
Paper • 2605.21800 • Published
Search is not available for this dataset
episode_idx int32 0 872 | step_idx int32 0 400 | proprio/joint_pos list | proprio/joint_vel list | proprio/effector_pos list | proprio/effector_yaw list | proprio/gripper_opening list | proprio/gripper_vel list | proprio/gripper_contact list | privileged/block_0_pos list | privileged/block_0_quat list | privileged/block_0_yaw list | privileged/block_1_pos list | privileged/block_1_quat list | privileged/block_1_yaw list | privileged/block_2_pos list | privileged/block_2_quat list | privileged/block_2_yaw list | privileged/block_3_pos list | privileged/block_3_quat list | privileged/block_3_yaw list | privileged/target_block list | privileged/target_block_pos list | privileged/target_block_yaw list | privileged/digit_0_value list | privileged/digit_0_pos list | privileged/digit_0_size list | privileged/digit_0_visible list | privileged/digit_count list | privileged/floor_material list | privileged/wall_material list | privileged/floor_rgb list | privileged/wall_rgb list | privileged/light_pos list | privileged/light_dir list | prev_qpos list | prev_qvel list | qpos list | qvel list | control list | time list | target list | success list | render_time list | pixels imagewidth (px) 224 224 | observation list | reward list | terminated list | truncated list | action list | id list | variation_agent_color list | variation_agent_ee_start_position list | variation_background_floor_material list | variation_background_floor_rgb list | variation_background_wall_material list | variation_background_wall_rgb list | variation_camera_angle_delta list | variation_cube_color list | variation_cube_goal_position list | variation_cube_goal_yaw list | variation_cube_size list | variation_cube_start_position list | variation_cube_start_yaw list | variation_digit_count list | variation_digit_position list | variation_digit_size list | variation_digit_value list | variation_digit_yaw list | variation_floor_color list | variation_light_ambient list | variation_light_diffuse list | variation_light_direction list | variation_light_headlight_diffuse list | variation_light_intensity list | variation_light_position list | variation_light_specular list |
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End of preview. Expand in Data Studio
OGBCubeDR: Domain-Randomized OGBench Cube-Quadruple Expert Dataset
5,000 episodes × 401 steps (224×224 RGB) of a scripted pick-and-place
expert on OGBench's cube-quadruple manipulation task, collected in the
swm/OGBCubeDR-v0 environment — an extension of swm/OGBCube-v0 with 22
domain-randomization axes (lighting, floor/wall materials, cube color/size,
digit decals, camera angle, agent color). It was built to train and evaluate
short-horizon, real-time Joint-Embedding Predictive Architecture (JEPA) world
models for model-predictive control under visual distribution shift.
Dataset Details
- Environment:
swm/OGBCubeDR-v0(stable-worldmodel), extending OGBench'scube-quadrupletask (4 cubes, pick-and-place / stacking). - Policy: scripted oracle (
CubePlanOracle, OGBench's-playoracle), biased toward stacking (p_stack=0.8) over 400-step episodes. - Randomization: per-episode resampling of all 22 axes — light position/ direction/color, floor/wall material, cube color/size/start/goal pose, camera angle offset, agent color, and digit decals with recorded ground-truth value/position/size/visibility for representation probing.
- Fields:
pixels,action,reward,terminated,truncated,success,qpos,qvel,episode_idx,step_idx,privileged/*(block positions, digit ground truth), andvariation_*(sampled randomization parameters per episode). - Format: LanceDB table (episode-contiguous), ~30 GB.
- Known quirk: the reset-frame placeholder action is rotated to each
episode's final step, so the last
actionper episode isNaNby design.
Intended Use
Training and evaluating latent world models (e.g. JEPA-style) for short-horizon, receding-horizon planning (CEM/MPPI-style MPC), and for probing whether visual world model embeddings retain physical/semantic structure (cube pose, digit identity) under domain shift.
Source Code
Collected with stable-worldmodel
(fork adding swm/OGBCubeDR-v0 and scripts/data/collect_cube_quadruple_dr_sharded.py
on top of upstream galilai-group/stable-worldmodel),
built on OGBench, for training
LeWorldModel (LeWM).
Citation
If you use this dataset, please cite all three:
@inproceedings{ogbench_park2025,
title={OGBench: Benchmarking Offline Goal-Conditioned RL},
author={Park, Seohong and Frans, Kevin and Eysenbach, Benjamin and Levine, Sergey},
booktitle={International Conference on Learning Representations (ICLR)},
year={2025},
}
@misc{maes_lld2026swm,
title = {stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation},
author = {Maes, Lucas and Le Lidec, Quentin and Facury, Luiz and Massaudi, Nassim and
Chaurasia, Ayush and Capuano, Francesco and Gao, Richard and Gillin, Taj and
Haramati, Dan and Scieur, Damien and LeCun, Yann and Balestriero, Randall},
year = {2026},
eprint = {2605.21800},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2605.21800},
}
@article{maes_lelidec2026lewm,
title={LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels},
author={Maes, Lucas and Le Lidec, Quentin and Scieur, Damien and LeCun, Yann and Balestriero, Randall},
journal={arXiv preprint arXiv:2603.19312},
year={2026}
}
License
MIT, inherited from OGBench and stable-worldmodel, both MIT-licensed.
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