
Word Embeddings as Metric Recovery in Semantic Spaces (2016) [pdf] - espeed
https://people.csail.mit.edu/tommi/papers/HasAlvJaa-TACL16.pdf
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trashtoss
Very late to see this but am curious how these approaches handle words with
numerous meanings (like run, which arguably has dozens if not hundreds of
idiomatic meanings in English).

Distinct vectors for each meaning? One vector and the metric still works
better than you'd think? It's not clear from the paper at a skim.

