Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space

EMNLP 2014 Arvind NeelakantanJeevan ShankarAlexandre PassosAndrew McCallum

There is rising interest in vector-space word embeddings and their use in NLP, especially given recent methods for their fast estimation at very large scale. Nearly all this work, however, assumes a single vector per word type ignoring polysemy and thus jeopardizing their usefulness for downstream tasks... (read more)

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