This paper presents a theoretical framework for understanding prompts in large language models (LLMs) through the lens of semiotics. It proposes that prompting is not merely a technical input but a dynamic communicative and epistemic act involving sign formation and interpretation. By applying Peirce's semiotic models, the research suggests that LLMs act as semiotic resources that co-construct meaning, thereby reshaping how knowledge is organized and accessed in digital environments. AI
IMPACT Reframes understanding of LLM interaction, potentially influencing future AI design and human-AI communication strategies.
RANK_REASON Academic paper published on arXiv discussing theoretical aspects of LLM prompting. [lever_c_demoted from research: ic=1 ai=1.0]
AI-generated summary · Google Gemini · from 1 sources. How we write summaries →
