Impact of Behavioral Instructions in Language Models

• Autores: Huamanchumo Trujillo, Francisco Gerardo, Campos Gamarra, Alejandro Roman, Torres Villanueva, Marcelino
• Formato: artículo
• Fecha de Publicación: 2024
• Institución: Universidad La Salle
• Repositorio: Revistas - Universidad La Salle
• Lenguaje: español
• OAI Identifier: oai:ojs.revistas.ulasalle.edu.pe:article/152
• Enlace del recurso: https://revistas.ulasalle.edu.pe/innosoft/article/view/152; https://doi.org/10.48168/innosoft.s16.a152; https://purl.org/42411/s16/a152; https://n2t.net/ark:/42411/s16/a152
• Nivel de acceso: acceso abierto
• Materia: Behavioral instructions; Languages and their Models; Human Language Processing; Model Performance; Language Comprehension; Text Applications; Model Configuration; Model Training; Machine translation; Text Generation; Document Classification; Intrucciones de comportamiento; Lenguajes y sus modelos; Procesado de lenguaje humano; Rendimeinto del Modelo; Comprension de los lenguajes; Aplicaciones de texto; Configuración del Modelo; Entrenamiento del Modelo; Traducción automática; Generación de texto; Clasificación de documentos

The impact of behavioral instructions on language models is a fundamental area of research in the field of processing for language that is human. This study focuses on analyzing how specific directions provided to language models affect their performance and efficiency on various tasks. It examines in detail the importance of instructions in the understanding for languages to be human and their influence on applications in activities such as machine translation, textual content creation, and document categorization. It discusses how behavioral instructions impact the configuration and training of models, as well as their predictive and generative capabilities. Concrete examples of how instructions can improve or limit the performance of linguistic models in different contexts are presented. The results obtained highlight the need to carefully consider behavioral instructions when developing and evaluating languages and their models, with the desire to optimize their accuracy and perform well on various linguistic tasks.