Sparse associative memory based on contextual code learning for disambiguating word senses
Max Raphael Sobroza,
Tales Marra,
Deok-Hee Kim-Dufor
et al.
Abstract:In recent literature, contextual pretrained Language Models (LMs) demonstrated their potential in generalizing the knowledge to several Natural Language Processing (NLP) tasks including supervised Word Sense Disambiguation (WSD), a challenging problem in the field of Natural Language Understanding (NLU). However, word representations from these models are still very dense, costly in terms of memory footprint, as well as minimally interpretable. In order to address such issues, we propose a new supervised biolo… Show more
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