3 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CL2021★ 2 cited
Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications
Haw-Shiuan Chang, Amol Agrawal, Andrew McCallum
Most unsupervised NLP models represent each word with a single point or single region in semantic space, while the existing multi-sense word embeddings cannot represent longer word…
cs.CL2018★ 3 cited
Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh +4
Word sense induction (WSI), which addresses polysemy by unsupervised discovery of multiple word senses, resolves ambiguities for downstream NLP tasks and also makes word representa…