Sentence Embeddings

PAUSE, or Positive and Annealed Unlabeled Sentence Embedding, is an approach for learning sentence embeddings from a partially labeled dataset. It is based on a dual encoder schema that is widely adopted in supervised sentence embedding training. Each individual sample $\mathbf{x}$ contains a pair of hypothesis and premise sentences $(x_{i},x^{\prime}_{i})$, each of which is fed into a pretrained encoder (e.g. BERT). As shown in Figure, the two encoders are identical during the training by sharing their weights.

Source: PAUSE: Positive and Annealed Unlabeled Sentence Embedding

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Sentence Embedding 1 50.00%
Sentence Embeddings 1 50.00%

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