Modelling Commonsense Commonalities with Multi-Facet Concept Embeddings

arXiv:2403.16984v1 Announce Type: cross
Abstract: Concept embeddings offer a practical and efficient mechanism for injecting commonsense knowledge into downstream tasks. Their core purpose is often not to predict the commonsense properties of concepts themselves, but rather to identify commonalities, i.e.\ sets of concepts which share some property of interest. Such commonalities are the basis for inductive generalisation, hence high-quality concept embeddings can make learning easier and more robust. Unfortunately, standard embeddings primarily reflect basic taxonomic categories, making them unsuitable for …

abstract arxiv concept concepts core cs.ai cs.cl embeddings facet identify knowledge modelling practical property tasks type