Pusula

From Zeroes to Meaning: Why Word Embeddings Crush One-Hot Vectors in NLP

Machines don’t understand words; they understand numbers. This simple fact presents the foundational challenge of Natural Language Processing (NLP): How do we convert the rich, nuanced, and contextual ...
Pusula

Mastering Natural Language Processing — Part 17 Understanding Word Embeddings: What They Are and How to Use Them with Python

Natural language processing (NLP) has evolved rapidly over the last decade, and one of the key breakthroughs that made this possible is word embeddings. If you’ve ever wondered how machines understand ...
Quanta Magazine

How ‘Embeddings’ Encode What Words Mean — Sort Of

A picture may be worth a thousand words, but how many numbers is a word worth? The question may sound silly, but it happens to be the foundation that underlies large language models, or LLMs — and ...
Nature

Predicting drug–gene relations via analogy tasks with word embeddings

Natural language processing is utilized in a wide range of fields, where words in text are typically transformed into feature vectors called embeddings. BioConceptVec is a specific example of ...
Nature

Compressed models for co-reference resolution: enhancing efficiency with debiased word embeddings

This work presents a comprehensive approach to reduce bias in word embedding vectors and evaluate the impact on various Natural Language Processing (NLP) tasks. Two GloVe variations (840B and 50) are ...