Papers with vector-based multi-head attention

1 papers
Enhancing Sentence Embedding with Generalized Pooling (C18-1)

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Challenge: Existing methods for learning sentence embedding are limited, but still need to be improved.
Approach: They propose a vector-based multi-head attention model that uses special cases of max pooling, mean pooling and scalar self-attention.
Outcome: The proposed model improves on natural language inference, author profiling, and sentiment classification tasks.

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