license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) solve mass version 12
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data.jsonl
Version 1
ARC-AGI Tasks where the job is to identify the mass of objects with a specific size.
example count: 2-4.
test count: 1-2.
image size: 4-6.
find mass: 1-2.
connectivity: ALL8.
Version 2
image size: 3-10.
Version 3
image size: 1-15.
Version 4
image size: 1-15.
find mass: 1-3.
Version 5
image size: 1-8.
find mass: 1-4.
Version 6
Compare mass of adjacent rows/columns. image size: 4-7. color count: 10.
This was something that the model struggles with. What if I use fewer colors and smaller images.
Version 7
Compare mass of adjacent rows/columns. image size: 4-6. color count: 2,3,10.
Still something that the model has difficulties with.
Version 8
Disabled comparing columns. Disable too many colors.
Focus is only on compare mass of adjacent rows. image size: 4-6. color count: 2.
Yay, the model groks this.
Version 9
Disabled comparing columns. Disable too many colors.
Focus is only on compare mass of adjacent columns. image size: 4-6. color count: 2.
This is hard for the model to make sense of.
Version 10
Still focus is only on compare mass of adjacent columns. image size: 3-5. color count: 2.
Version 11
Focus on adjacent rows/columns. image size: 3-8. color count: 2,3,10.
Version 12
Bigger images. image size: 3-12.