Learning to identify and encode entities with deep learning models 

Sorodoc, Ionut-Teodor (Data de defensa: 2022-04-11)

In this thesis, I tackle the ability of deep neural networks to represent entities, and I assess the extent to which this feature impacts tasks involving entities. I consider two standard architectures, LSTM and Transformer, ...