Papers with post-processing model

1 papers
Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources (N18-1)

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Challenge: Word vector specialisation is a portable, light-weight approach to fine-tuning distributional word vector spaces by injecting external knowledge from rich lexical resources such as WordNet.
Approach: They propose a constraint-driven vector space specialisation method that embeds external knowledge into lexical resources into a deep neural network to specialise unseen words.
Outcome: The proposed method preserves useful linguistic knowledge for seen words while propagating external signal to unseen words to improve their vector representations.

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