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SimpleICL
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Semantic-Discrimination-Test-Set

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robotics
in-context-learning
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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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Semantic-Discrimination-Test-Set

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

Semantic Discrimination Test Set

We do not construct our dataset using the full set of RoboTwin tasks, as fragile objects such as bottle are particularly prone to collisions in the dense-object settings designed for ICL, which can interfere with task execution.

The test data is collected via our tailored SimpleICL data pipeline, which is not the official RoboTwin setting.

Directory structure

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

In this test set, each test episode is reorganized as:

<task_name>__<serial_number>/
  placement0/
    <task_name>/<embodiment>
        data/
        instructions/
        video/
        scene_info.json
      placement_meta.json
  completion.json
  manifest.json

This removes all tasks unrelated to the evaluation, saves storage space, and still allows the framework designed for the aforementioned data structures to read the data.

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/Semantic-Discrimination-Test-Set