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 grid version 7
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 extract content from a grid.

example count: 2-4.

test count: 1-2.

image size: 2-4.

cell size: 1-5.

grid line size: 1.

# Version 2

image size: 2-5.

cell size: 1-6.

grid line size: 1-2.

# Version 3

Added `generate_task_mutate_content_inside_grid`, that does `flipx`, `flipy`, `rotate 180`, while preserving the grid.

# Version 4

Extended `generate_task_extract_content_from_grid` so it does mutations of the output: flip x/y/a/b, rotate cw/ccw/180.

# Version 5

Earlier predictions added to some of the rows.

# Version 6

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

# Version 7

Replaced RLE compressed response with raw pixel response.