SHAPES-SyGeT (SHAPES Systematic Generalization Test) is a split of the SHAPES dataset [1] that can be used to evaluate systematic generalization.
- is a
COLOR
shapeTRANSFORM
aCOLOR
shape - is a
SHAPE
TRANSFORM
aCOLOR
shape - is a
SHAPE
TRANSFORM
TRANSFORM
aCOLOR
shape - is a
SHAPE
TRANSFORM
TRANSFORM
aSHAPE
- is a
COLOR
shape aSHAPE
- is a
SHAPE
COLOR
- is a
SHAPE
aSHAPE
- is a
COLOR
shapeTRANSFORM
TRANSFORM
aCOLOR
shape - is a
COLOR
shapeTRANSFORM
aSHAPE
- is a
COLOR
shapeTRANSFORM
TRANSFORM
aSHAPE
- is a
SHAPE
TRANSFORM
aSHAPE
- is a
COLOR
shapeCOLOR
COLOR
can take values in 'red', 'green', 'blue'
SHAPE
can take values in 'circle', 'triangle', 'square'
TRANSFORM
can take values in 'above', 'below', 'left of', 'right of'
Train
and Val-IID
use train templates. Val-OOD
uses evaluation templates.
Train
size: 7560
Val-IID
size: 1080
Val-OOD
size: 6976
[1] Jacob Andreas, Marcus Rohrbach, Trevor Darrell, and Dan Klein. “Neural module networks.” In: Proceedings of the IEEE conference on computer vision and pattern recognition. 2016, pp. 39–48.