用多智能体LLM辅助创作者构建有互动关系的角色群像
Constella: Supporting Storywriters' Interconnected Character Creation through LLM-based Multi-Agents
- 基于大模型的多智能体系统，模拟角色间关系
- 支持角色关联发现、内心独白展示与互动反馈
- 适合需要复杂角色网络的长篇故事创作者
在长篇故事创作中，关注角色之间的关系动态至关重要。我们对14位写作者的初步研究发现，他们难以构思能影响已有角色的新角色，难以平衡角色间的相似与差异，并细致刻画角色关系。基于此，我们设计了Constella——一个基于大语言模型的多智能体工具，支持角色互联创作。该工具提供三个功能：角色关联发现（FRIENDS DISCOVERY）、多角色内心独白展示（JOURNALS）和角色间互动回应（COMMENTS）。为期7-8天的部署研究（N=11）表明，Constella帮助创作者构建了复杂的角色群体，促进了对角色思想与情感的对比分析，并深化了对角色关系的理解。研究指出，多智能体交互可有效分配创作者在角色群中的注意力与精力。
原文摘要 · Abstract (English)
Creating a cast of characters by attending to their relational dynamics is a critical aspect of most long-form storywriting. However, our formative study (N=14) reveals that writers struggle to envision new characters that could influence existing ones, balance similarities and differences among characters, and intricately flesh out their relationships. Based on these observations, we designed Constella, an LLM-based multi-agent tool that supports storywriters' interconnected character creation process. Constella suggests related characters (FRIENDS DISCOVERY feature), reveals the inner mindscapes of several characters simultaneously (JOURNALS feature), and manifests relationships through inter-character responses (COMMENTS feature). Our 7-8 day deployment study with storywriters (N=11) shows that Constella enabled the creation of expansive communities composed of related characters, facilitated the comparison of characters' thoughts and emotions, and deepened writers' understanding of character relationships. We conclude by discussing how multi-agent interactions can help distribute writers' attention and effort across the character cast.
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