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 …

Abstract Word Usage Graphs (WUGs) represent human semantic proximity judgments for
pairs of word uses in a weighted graph, which can be clustered to infer word sense clusters …

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

In the universe of Natural Language Processing, Transformer-based language models like
BERT and (Chat) GPT have emerged as lexical superheroes with great power to solve open …

Detecting temporal semantic changes of words is an important task for various NLP
applications that must make time-sensitive predictions. Lexical Semantic Change Detection …

We asked task participants to solve two subtasks given a pair of word usages: Ordinal
Graded Word-in-Context Classification (OGWiC) and Disagreement in Word-in-Context …

We present the DURel tool that implements the annotation of semantic proximity between
uses of words into an online, open source interface. The tool supports standardized human …

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

Modeling lexical semantics is a challenging task, often suffering from interpretability pitfalls.
In this paper, we delve into the generation of dictionary-like sense definitions and explore …

There has been a surge of interest in computational modeling of semantic change. The foci
of previous works are on detecting and interpreting word senses gained over time; however …