Over the past years, distributed semantic representations have proved to be effective and
flexible keepers of prior knowledge to be integrated into downstream applications. This …

Polysemy is the type of lexical ambiguity where a word has multiple distinct but related
interpretations. In the past decade, it has been the subject of a great many studies across …

Recent work has shown that the integration of visual information into text-based models can
substantially improve model predictions, but so far only visual information extracted from …

Pre-trained language models (LMs) encode rich information about linguistic structure but
their knowledge about lexical polysemy remains unclear. We propose a novel experimental …

Vector-based word representation paradigms situate lexical meaning at different levels of
abstraction. Distributional and static embedding models generate a single vector per word …

We propose a framework that extends synchronic polysemy annotation to diachronic
changes in lexical meaning, to counteract the lack of resources for evaluating computational …

Word meaning is notoriously difficult to capture, both synchronically and diachronically. In
this paper, we describe the creation of the largest resource of graded contextualized …

Most work on word sense disambiguation has assumed that word usages are best labeled
with a single sense. However, contextual ambiguity or fine-grained senses can potentially …

In this paper, we propose an unsupervised and automated method to identify noun sense
changes based on rigorous analysis of time-varying text data available in the form of millions …

Word sense disambiguation (WSD) is an old and important task in computational linguistics
that still remains challenging, to machines as well as to human annotators. Recently there …