Natural Language Processing: An Overview of Models, Transformers and Applied Practices

Santiago Canchila1, Carlos Meneses-Eraso2, Javier Casanoves-Boix3, Pascual Cortés-Pellicer4 and Fernando Castelló-Sirvent5

  1. Universidad Sergio Arboleda
    Calle 74 No. 14 - 14 Bogotá, Colombia
    santiago.canchila01@usa.edu.co
  2. Universidad Sergio Arboleda
    Calle 74 No. 14 - 14 Bogotá, Colombia
    carlos.meneses@usa.edu.co
  3. Universidad Alfonso X El Sabio
    Avda. de la Universidad, 1. Villanueva de la Cañada, 28691, Madrid, Spain
    jcasaboi@uax.es
  4. Department of Business Management Universitat Politècnica de València (UPV)
    Camí de Vera, s/n - 46022 València, Spain
    pascorpe@omp.upv.es
  5. Department of Business Management Universitat Politècnica de València (UPV)
    Camí de Vera, s/n - 46022 València, Spain
    fernando.castello@upv.es

Abstract

The study of utilizing human language in computer systems referred to as NLP, is becoming increasingly significant in various aspects of life, including research, daily activities, commerce, and entrepreneurship endeavors. A multitude of tech companies are dedicating resources towards the development and improvement of NLP methods, models, and products. To add to that, open-source contributions to the field are on the rise. However, with so much progress being made, it may be challenging to understand the current state of NLP and what models are considered to be the most efficient. To help those grappling with the fast-paced and constantly evolving NLP landscape, we have put together a comprehensive overview of the latest NLP research and advancements.

Key words

NLP, Deep Learning, Transformers

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS230217031C

Publication information

Volume 21, Issue 3 (June 2024)
Year of Publication: 2024
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

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How to cite

Canchila, S., Meneses-Eraso, C., Casanoves-Boix, J., Cortés-Pellicer, P., Castelló-Sirvent, F.: Natural Language Processing: An Overview of Models, Transformers and Applied Practices. Computer Science and Information Systems, Vol. 21, No. 3, 917-965. (2024), https://doi.org/10.2298/CSIS230217031C