Showing 2019Show all
2 papers · 1 filter
cs.CL2019
Putting words in context: LSTM language models and lexical ambiguity
Laura Aina, Kristina Gulordava, Gemma Boleda
In neural network models of language, words are commonly represented using context-invariant representations (word embeddings) which are then put in context in the hidden layers. S…
cs.CL2019
What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue
Laura Aina, Carina Silberer, Matthijs Westera +2
Humans use language to refer to entities in the external world. Motivated by this, in recent years several models that incorporate a bias towards learning entity representations ha…