Papers with unsupervised single methods

1 papers
Learning Universal Sentence Representations with Mean-Max Attention Autoencoder (D18-1)

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Challenge: Existing methods to learn universal sentence representations focus on supervised learning.
Approach: They propose a mean-max attention autoencoder that uses a multi-head mechanism to reconstruct the input sequence.
Outcome: The proposed model outperforms state-of-the-art unsupervised single methods on a wide range of 10 transfer tasks.

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