Towards Generalizable Sentence Embeddings

@inproceedings{Triantafillou2016TowardsGS,
  title={Towards Generalizable Sentence Embeddings},
  author={Eleni Triantafillou and Jamie Ryan Kiros and Raquel Urtasun and Richard S. Zemel},
  booktitle={Rep4NLP@ACL},
  year={2016}
}
In this work, we evaluate different sentence encoders with emphasis on examining their embedding spaces. Specifically, we hypothesize that a “high-quality” embedding aids in generalization, promoting transfer learning as well as zero-shot and one-shot learning. To investigate this, we modify Skipthought vectors to learn a more generalizable space by exploiting a small amount of supervision. The aim is to introduce an additional notion of similarity in the embeddings, rendering the vectors… 

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