1 citations · 1 across the 9 of their papers we have counts for
5 papers · 1 filter
Montague semantics and modifier consistency measurement in neural language models
Danilo S. Carvalho, Edoardo Manino, Julia Rozanova +2
This work proposes a novel methodology for measuring compositional behavior in contemporary language embedding models. Specifically, we focus on adjectival modifier phenomena in ad…
Estimating productivity gains in digital automation
Mauricio Jacobo-Romero, Danilo S. Carvalho, André Freitas
This paper proposes a novel productivity estimation model to evaluate the effects of adopting Artificial Intelligence (AI) components in a production chain. Our model provides evid…
Quasi-symbolic Semantic Geometry over Transformer-based Variational AutoEncoder
Yingji Zhang, Danilo S. Carvalho, André Freitas
Formal/symbolic semantics can provide canonical, rigid controllability and interpretability to sentence representations due to their \textit{localisation} or \textit{composition} p…
Learning Disentangled Representations for Natural Language Definitions
Danilo S. Carvalho, Giangiacomo Mercatali, Yingji Zhang +1
Disentangling the encodings of neural models is a fundamental aspect for improving interpretability, semantic control and downstream task performance in Natural Language Processing…
Systematicity, Compositionality and Transitivity of Deep NLP Models: a Metamorphic Testing Perspective
Edoardo Manino, Julia Rozanova, Danilo Carvalho +2
Metamorphic testing has recently been used to check the safety of neural NLP models. Its main advantage is that it does not rely on a ground truth to generate test cases. However,…