Do Influence Tactics Matter? Investigating Prompt Framing Effects in LLM Code Generation
Large Language Models (LLMs) are increasingly integrated into software engineering workflows, helping developers write, debug, test, and maintain code. While prompt wording and structure are known to influence model performance, the impact of psychologically inspired prompt framings remains unexplored. This study investigates whether different psychology-based communication strategies that humans use to persuade or motivate others can lead to more effective prompt framing, which may, in turn, affect LLM behaviour in coding tasks. Drawing on Yukl & Falbe's well-known taxonomy, we operationalized eight influence tactics (like rational persuasion, ingratiation, and exchange) into reproducibl...
| Authors | Alex Deaconu, Anubhav Gupta, Manaal Basha et al. |
|---|---|
| Primary category | cs.SE |
| Published | 11 August 2026 |
| Last updated at source | 11 August 2026 |
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