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Datasets:
SimpleICL
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Raw-ICL-oriented-Training-Set

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Tags:
robotics
in-context-learning
License:
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The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 84, in _split_generators
                  raise ValueError(
                  ...<2 lines>...
                  )
              ValueError: The TAR archives of the dataset should be in WebDataset format, but the files in the archive don't share the same prefix or the same types.
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ~~~~~~~~~~~~~~~~~~~~~~~^
                      path=dataset,
                      ^^^^^^^^^^^^^
                      config_name=config,
                      ^^^^^^^^^^^^^^^^^^^
                      token=hf_token,
                      ^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
                  info = get_dataset_config_info(
                      path,
                  ...<6 lines>...
                      **config_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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Raw-ICL-oriented-Training-Set

This repository releases the training resources of the paper “In-context Robot Learning Made Simple: A Democratized Recipe for Manipulation Tasks”

Raw Training Set

This dataset contains the full collection of training data generated by our SimpleICL data pipeline.

The data is released in its original form, without conversion to the LeRobot format or data cleaning, to facilitate broader reuse and support diverse research applications beyond SimpleICL.

Directory structure

The raw data is stored in shards:

dual_arm_multi_perturb_1/
  <scene_name1>.tar.gz
  <scene_name2>.tar.gz
  ...
dual_arm_multi_perturb_2/
dual_arm_multi_perturb_3/
...

After extraction, our SimpleICL data pipeline produces episodes that are organized as:

<scene_name>/
  placement0/			# One scene -> Multi-placement
    <task0_name>/		# One placement -> Multi-task
      <embodiment>[__pert0]/	# One task -> Multi-perturbation
        data/
          episode<I>.hdf5		
        instructions/
          episode<I>.json
        video/
          episode<I>.mp4		# One perturbation -> Multi-visual-variant
        scene_info.json	# Task-level meta info
      <embodiment>[__pert1]/
      ...
    <task1_name>/
    ...
    placement_meta.json	# Placement-level meta info
  placement1/
  ...
  completion.json 		# Collection completion markup
  manifest.json 		# Scene configuration

Project

Citation 

@article{li2026context,
  title={In-context Robot Learning Made Simple: A Democratized Recipe for Manipulation Tasks},
  author={Li, Minxing and Han, Minghao and Zhao, Weizhi and Wang, Hanwen and Liu, Xiangshuo and Shang, Shuyao and Zhou, Jingxiang and Sun, Mingchao and Pan, Hongyu and Xu, Mu and others},
  journal={arXiv preprint arXiv:2609.38173},
  year={2026}
}

License

This release is a derivative of RoboTwin 2.0 framework for ICL-oriented data collection.

It is released under the MIT license, consistent with the upstream RoboTwin 2.0 release. Please also refer to the original RoboTwin project and dataset for upstream attribution and terms.

RoboTwin repository: https://github.com/RoboTwin-Platform/RoboTwin
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Paper for SimpleICL/Raw-ICL-oriented-Training-Set