Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions. (arXiv:2305.07303v1 [cs.CL])

Neural-based word embeddings using solely distributional information have
consistently produced useful meaning representations for downstream tasks.
However, existing approaches often result in representations that are hard to
interpret and control. Natural language definitions, on the other side, possess
a recursive, self-explanatory semantic structure that can support novel
representation learning paradigms able to preserve explicit conceptual
relations and constraints in the vector space.

This paper proposes a neuro-symbolic, multi-relational framework to learn
word embeddings exclusively from natural language definitions by jointly …

arxiv control definitions embeddings information language meaning natural natural language novel recursive representation representation learning semantic support word word embeddings