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Autor principal: Bubas, Goran
Formato: Preprint
Publicado: 2025
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Acceso en línea:https://arxiv.org/abs/2511.02838
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author Bubas, Goran
author_facet Bubas, Goran
contents A concise overview is provided of selected theoretical models of communication competence in the fields of linguistics, interpersonal communication, second language use, and human-robot interaction. The following practical research consisted of two case studies with the goals of investigating how advanced AI tools like ChatGPT and Gemini interpret elements of two communication competence theories in the context of Large Language Model (LLM) interactions with users. The focus was on these theoretical approaches: (1) an integrated linguistic-interpersonal model and (2) an interpersonal "human-humanoid" interaction model. The conclusion is that both approaches are suitable for a better understanding of LLM-user interaction.
format Preprint
id arxiv_https___arxiv_org_abs_2511_02838
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle How ChatGPT and Gemini View the Elements of Communication Competence of Large Language Models: A Pilot Study
Bubas, Goran
Human-Computer Interaction
A concise overview is provided of selected theoretical models of communication competence in the fields of linguistics, interpersonal communication, second language use, and human-robot interaction. The following practical research consisted of two case studies with the goals of investigating how advanced AI tools like ChatGPT and Gemini interpret elements of two communication competence theories in the context of Large Language Model (LLM) interactions with users. The focus was on these theoretical approaches: (1) an integrated linguistic-interpersonal model and (2) an interpersonal "human-humanoid" interaction model. The conclusion is that both approaches are suitable for a better understanding of LLM-user interaction.
title How ChatGPT and Gemini View the Elements of Communication Competence of Large Language Models: A Pilot Study
topic Human-Computer Interaction
url https://arxiv.org/abs/2511.02838