We will talk in detail about Abstract Meaning Representation (AMR), a form of deep semantic parsing that allows a detailed but flexible representation of the semantics of one or more sentences, capturing "who does what to whom". The talk first introduces the formalism of AMR graphs and its properties. We will focus on how changes in textual input reflect in the AMR and its compositional properties as a means of capturing sentence variations. This will be followed by an overview of state-of-the art approaches for the main related machine learning tasks: AMR parsing and AMR-to-text. Finally, the incorporation of structure to large language models for AMR parsing will be presented as an example of SoTA AMR parsing.
Texto informado pelo autor.
* Os participantes dos seminários não poderão acessar às dependências da FGV usando bermuda, chinelos, blusa modelo top ou cropped, minissaia ou camiseta regata. O uso da máscara é facultativo, porém é obrigatória a apresentação do comprovante de vacinação (físico ou digital).
Apoiadores / Parceiros / Patrocinadores
Ramon Astudillo - I am currently Principal Research Staff Member at IBM Research AI in the T. J. Watson research center in Yorktown Heights, New York. Before this I was senior Research Scientist at Unbabel and associate researcher at INESC-ID in Lisboa and before that PhD candidate at TU Berlin. I got here starting from signal processing, then speech recognition and then natural language processing. While at it, deep learning happened. I ended up spending very large chunks of my life in Spain, Germany and Portugal and now in the Unites States. It is hard to find things that do not interest me, but artificial and crowd intelligence seem particularly motivating in this moment in history.
a) Opção presencial
Fundação Getulio Vargas *
Praia de Botafogo, 190 - sala 537
b) Opção remota (via Zoom)
Meeting ID: 981 5075 6795
Tel: 55 21 3799-5917