Learning Word Embeddings
23 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Learning Word Embeddings
Most implemented papers
InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity
We study the objective in the limit as T goes to infinity, which allows us to simplify the expression of Qiu et al. We prove that this limiting objective corresponds to factoring a simple transformation of the pseudoinverse of the graph Laplacian, linking DeepWalk to extensive prior work in spectral graph embeddings.
ViCE: Improving Dense Representation Learning by Superpixelization and Contrasting Cluster Assignment
Recent self-supervised models have demonstrated equal or better performance than supervised methods, opening for AI systems to learn visual representations from practically unlimited data.
Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions
Natural language definitions possess a recursive, self-explanatory semantic structure that can support representation learning methods able to preserve explicit conceptual relations and constraints in the latent space.
