Syntactic Transformation in Large Language Models (LLMs): A Transformational Generative Grammar (TGG) Perspective

This paper investigates the syntactic transformation in Large Language Models (LLMs) using Chomsky’s Transformational Generative Grammar Theory (TGG) as a tool of examination. The current paper focuses on the textual analysis of LLMs-generated text to examine the incapability of innateness and high-tech plagiarized content. The analysis of the generated responses of LLMs shows the inability to generate human-like text and the possibility of plagiarized content. It further highlights the limitations and ethical considerations surrounding the use of LLMs-generated text in academia necessitating the establishment of roles and regulations for author work integrity and accountability.