task_categories:image-to-text task_categories:text-to-image language:en license:mit size_categories:1K<n<10K format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) solve mask version 8
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: data.jsonl
---

# Version 1

ARC-AGI Tasks where the job is to repair the masked areas/rectangles.

example count: 2-4.

test count: 1-2.

image size: 4-7.

noise: 0.1, 0.2.

There are these transformations: `identify_the_masked_area`, `repair_the_masked_area`

# Version 2

image size: 4-10.

# Version 3

image size: 4-13.

# Version 4

Still having all the other transformations enabled.

Added `generate_task_repair_rectangle_and_crop`.

input image size: 4-8.

mask size: 2-3.

# Version 5

Bigger images.

`generate_task_repair_rectangle_and_crop`: image size: 4-10. crop size: 2-4.

`generate_task_linepatterns_with_masked_areas`: image size: 4-15.

# Version 6

Earlier predictions added to some of the rows.

Smaller images. `generate_task_repair_rectangle_and_crop`: image size: 4-8. crop size: 2-4.

Smaller images. `generate_task_linepatterns_with_masked_areas`: image size: 4-12.

# Version 7

Added fields: `arc_task`, `test_index`, `earlier_output`.

# Version 8

Replaced RLE compressed response with raw pixel response.

Big images. `generate_task_repair_rectangle_and_crop`: image size: 4-10. crop size: 2-6.

Big images. `generate_task_linepatterns_with_masked_areas`: image size: 4-15.
