Natural language input in deep learning is commonly represented as embeddings. While embeddings are widely used, fundamental questions about the nature and purpose of embeddings remain. Drawing on traditional computational linguistics as well as parallels between language and vision, I will address two of these questions in this talk.

(1) Which linguistic units should be represented as embeddings?

(2) What are we trying to achieve using embeddings and how do we measure success?

If you would like to meet with the speaker, please contact Alessandra Zarcone.