Papers with Probabilistic FastText
Probabilistic FastText for Multi-Sense Word Embeddings (P18-1)
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| Challenge: | Probabilistic FastText model for word embeddings captures word senses, sub-word structure, and uncertainty information. |
| Approach: | They propose a model for word embeddings that captures multiple word senses . they represent each word with a Gaussian mixture density, with each vector representing an n-gram . |
| Outcome: | The proposed model outperforms dictionary-level probabilistic embeddings on word-similarity benchmarks. |