Semantic Shift Detection (SSD) is the task of identifying, interpreting, and assessing the
possible change over time in the meanings of a target word. Traditionally, SSD has been …

We present the first shared task on semantic change discovery and detection in Spanish and
create the first dataset of Spanish words manually annotated for semantic change using the …

Lexical Semantic Change (LSC) is the task of identifying, interpreting, and assessing the
possible change over time in the meanings of a target word. Traditionally, LSC has been …

Contextualized embeddings are the preferred tool for modeling Lexical Semantic Change
(LSC). Current evaluations typically focus on a specific task known as Graded Change …

This paper describes the organization and findings of AXOLOTL'24, the first multilingual
explainable semantic change modeling shared task. We present new sense-annotated …

The study of semantic shift, that is, of how words change meaning as a consequence of
social practices, events and political circumstances, is relevant in Natural Language …

There has been extensive work on human word sense annotation, ie, manually labeling
word uses in natural texts according to their senses. Such labels were primarily created for …

In this paper, we investigate automatic detection of subtle semantic shifts between social
communities of different political convictions in Dutch and English. We perform a …

This study addresses the task of Unknown Sense Detection in English and Swedish. The
primary objective of this task is to determine whether the meaning of a particular word usage …

This paper describes our solution of the first subtask from the AXOLOTL-24 shared task on
Semantic Change Modeling. The goal of this subtask is to distribute a given set of usages of …