تقرير
LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play
| العنوان: | LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play |
|---|---|
| المؤلفون: | Lu, Li-Chun, Chen, Shou-Jen, Pai, Tsung-Min, Yu, Chan-Hung, Lee, Hung-yi, Sun, Shao-Hua |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Artificial Intelligence |
| الوصف: | 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. Comment: 10 pages, 6 figures, Under review as a conference paper at COLM 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2405.06373 |
| رقم الأكسشن: | edsarx.2405.06373 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |