Abstract--Recent advancements in large language models tester receives the initial prompt detailing its role-setting, its (LLMs) have highlighted the potential for vulnerability detection, task, and the code segment to analyze. The tester is asked to a crucial component of software quality assurance. The response viewpoints from different roles in a typical software development is constrained by a maximum token limit, ensuring that the life-cycle, including both developers and testers. Preliminary evaluation of this approach indicates iterative output exchange in an attempt to reach a collectively a 13.48% increase in the precision rate, an 18.25% increase multi-perspective consensus inside the code review team. in the recall rate, and a 16.13% increase in the F1 score. The tester and the developer, equipped with their unique perspective and judgments, enter a dialectic interaction, aimed Keywords-large language models; vulnerability detection; at exploring and resolving different opinions on potential prompt engineering; software quality assurance vulnerabilities.

Large language models (LLMs) have shown exceptional proficiency in natural language processing but often fall short of generating creative and original responses to open-ended questions. To enhance LLM creativity, our key insight is to emulate the human process of inducing collective creativity through engaging discussions with participants from diverse backgrounds and perspectives. To this end, we propose LLM Discussion, a three-phase discussion framework that facilitates vigorous and diverging idea exchanges and ensures convergence to creative answers. Moreover, we adopt a role-playing technique by assigning distinct roles to LLMs to combat the homogeneity of LLMs. We evaluate the efficacy of the proposed framework with the Alternative Uses Test, Similarities Test, Instances Test, and Scientific Creativity Test through both LLM evaluation and human study. Our proposed framework outperforms single-LLM approaches and existing multi-LLM frameworks across various creativity metrics.