Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks

  title={Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks},
  author={Yossi Adi and Einat Kermany and Yonatan Belinkov and Ofer Lavi and Yoav Goldberg},
There is a lot of research interest in encoding variable length sentences into fixed length vectors, in a way that preserves the sentence meanings. Two common methods include representations based on averaging word vectors, and representations based on the hidden states of recurrent neural networks such as LSTMs. The sentence vectors are used as features for subsequent machine learning tasks or for pre-training in the context of deep learning. However, not much is known about the properties… CONTINUE READING
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