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Dataset Card for "scan"
Dataset Summary
SCAN tasks with various splits.
SCAN is a set of simple language-driven navigation tasks for studying compositional learning and zero-shot generalization.
See https://github.com/brendenlake/SCAN for a description of the splits.
Example usage: data = datasets.load_dataset('scan/length')
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
addprim_jump
- Size of downloaded dataset files: 18.69 MB
- Size of the generated dataset: 4.05 MB
- Total amount of disk used: 22.73 MB
An example of 'train' looks as follows.
addprim_turn_left
- Size of downloaded dataset files: 18.69 MB
- Size of the generated dataset: 4.09 MB
- Total amount of disk used: 22.76 MB
An example of 'train' looks as follows.
filler_num0
- Size of downloaded dataset files: 18.69 MB
- Size of the generated dataset: 2.85 MB
- Total amount of disk used: 21.53 MB
An example of 'train' looks as follows.
filler_num1
- Size of downloaded dataset files: 18.69 MB
- Size of the generated dataset: 3.14 MB
- Total amount of disk used: 21.82 MB
An example of 'train' looks as follows.
filler_num2
- Size of downloaded dataset files: 18.69 MB
- Size of the generated dataset: 3.44 MB
- Total amount of disk used: 22.12 MB
An example of 'train' looks as follows.
Data Fields
The data fields are the same among all splits.
addprim_jump
commands: astringfeature.actions: astringfeature.
addprim_turn_left
commands: astringfeature.actions: astringfeature.
filler_num0
commands: astringfeature.actions: astringfeature.
filler_num1
commands: astringfeature.actions: astringfeature.
filler_num2
commands: astringfeature.actions: astringfeature.
Data Splits
| name | train | test |
|---|---|---|
| addprim_jump | 14670 | 7706 |
| addprim_turn_left | 21890 | 1208 |
| filler_num0 | 15225 | 1173 |
| filler_num1 | 16290 | 1173 |
| filler_num2 | 17391 | 1173 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Citation Information
@inproceedings{Lake2018GeneralizationWS,
title={Generalization without Systematicity: On the Compositional Skills of
Sequence-to-Sequence Recurrent Networks},
author={Brenden M. Lake and Marco Baroni},
booktitle={ICML},
year={2018},
url={https://arxiv.org/pdf/1711.00350.pdf},
}
Contributions
Thanks to @lewtun, @patrickvonplaten, @mariamabarham, @thomwolf for adding this dataset.
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