Syntactic Transformation in Large Language Models (LLMs): A Transformational Generative Grammar (TGG) Perspective
Year: 2025
Type: article
Abstract: 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.
Source: Dibon Journal of Languages
DOI: 10.64169/djl.23
Author: Muhammad Farooq Khan
Institution: University of Peshawar
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411468147