Learning Semantic Representations
12 papers with code • 0 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Learning Semantic Representations
Edge-Map-345C
Most implemented papers
Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge
DannyMerkx/speech2image
•
•
CMCL (ACL) 2022
In this paper we create visually grounded word embeddings by combining English text and images and compare them to popular text-based methods, to see if visual information allows our model to better capture cognitive aspects of word meaning.
Unsupervised Object Representation Learning using Translation and Rotation Group Equivariant VAE
Here, we consider the problem of learning semantic representations of objects that are invariant to pose and location in a fully unsupervised manner.
