With the multiplication of social media platforms, which offer anonymity, easy access and
online community formation and online debate, the issue of hate speech detection and …

Abstract The realm of Natural Language Processing and Text Mining has seen a surge in
interest from researchers in hate speech detection, leading to an increase in related studies …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous word in a
particular context. Traditional supervised methods rarely take into consideration the lexical …

Abstract Word Sense Disambiguation is a long-standing task in Natural Language
Processing, lying at the core of human language understanding. However, the evaluation of …

A major obstacle in Word Sense Disambiguation (WSD) is that word senses are not
uniformly distributed, causing existing models to generally perform poorly on senses that are …

Contextual embeddings represent a new generation of semantic representations learned
from Neural Language Modelling (NLM) that addresses the issue of meaning conflation …

Contextual representations of words derived by neural language models have proven to
effectively encode the subtle distinctions that might occur between different meanings of the …

Abstract Word Sense Disambiguation models exist in many flavors. Even though supervised
ones tend to perform best in terms of accuracy, they often lose ground to more flexible …

Most of the existing pre-trained language representation models neglect to consider the
linguistic knowledge of texts, which can promote language understanding in NLP tasks. To …