Papers with gloss representation

1 papers
Leveraging Gloss Knowledge in Neural Word Sense Disambiguation by Hierarchical Co-Attention (D18-1)

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Challenge: Existing models for Word Sense Disambiguation use labeled data, but lack gloss knowledge.
Approach: They propose a co-attention mechanism to generate co-dependent representations for context and gloss . they propose to incorporate gloss knowledge into neural networks for Word Sense Disambiguation .
Outcome: The proposed model achieves state-of-the-art results on standard English all-words WSD datasets.

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