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Found 2 papers, 1 papers with code
A Mixture-of-Experts Model for Learning Multi-Facet Entity Embeddings
This is exploited by an associated gating network, which uses pre-trained word vectors to encourage the properties that are modelled by a given embedding to be semantically coherent, i. e. to encourage each of the individual embeddings to capture a meaningful facet.
Learning Conceptual Spaces with Disentangled Facets
To address this gap, we analyze how, and to what extent, a given vector space embedding can be decomposed into meaningful facets in an unsupervised fashion.
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