Lilja Øvrelid

TL;DR: This paper surveys the current state of academic research related to diachronic word embeddings and semantic shifts detection, and proposes several axes along which these methods can be compared, and outlines the main challenges before this emerging subfield of NLP.

TL;DR: A survey of the current state of academic research related to diachronic word embeddings and semantic shifts detection can be found in this article, where the authors discuss the notion of semantic shifts, and then continue with an overview of the existing methods for tracing such time-related shifts with word embedding models.

TL;DR: This article explores a combination of deep and shallow approaches to the problem of resolving the scope of speculation and negation within a sentence, specifically in the domain of biomedical research literature and shows that although both approaches perform well in isolation, even better results can be obtained by combining them.

TL;DR: This work proposes a fully automated conversion procedure from (logical-form) meaning representation to bilexical semantic dependencies, and seeks to shed light on the representational 'distance' between pure bileXical dependencies and full-blown logical-form propositional semantics.