Papers with neural-probabilistic model
Disambiguated skip-gram model (D18-1)
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| Challenge: | Disambiguated skip-gram is a neural-probabilistic model for learning multi-sense word embeddings. |
| Approach: | They propose a model that is end-to-end differentiable and can be interpreted as a feed-forward neural network. |
| Outcome: | The proposed model improves state-of-the-art in word sense induction benchmarks. |