Jokeasy：探索主题笑话生成中的人机协作
Jokeasy: Exploring Human-AI Collaboration in Thematic Joke Generation
AI总结：
Jokeasy通过人机协作提升主题笑话生成，结合搜索功能与双角色LLM代理，优化创意流程与素材整合。
摘要：
主题笑话是单口喜剧、情景喜剧和公开演讲的核心，其中情境和笑点依赖于新鲜的素材——新闻、轶事和文化参考，这些内容能引起观众共鸣。近年来，大语言模型（LLM）的进步使通过对话界面实现互动式笑话生成成为可能。尽管LLM能够实现互动式笑话生成，但普通的对话界面很少能给创作者足够的自主权、控制力或及时访问此类素材的机会来构建情境和笑点。我们设计了Jokeasy，一个具备搜索功能的原型系统，该系统集成了一个双角色LLM代理，充当素材猎人和原型作家，以支持主题笑话写作中的人机协作。Jokeasy提供了一个视觉画布，在此画布上检索到的网络内容被组织成可编辑的灵感块，并通过多阶段工作流程进行开发。一项包含13名业余爱好者和5名专家参与者（包括专业喜剧演员和HCI/AI专家）的定性研究显示，将实时网络素材融入这一结构化工作流程丰富了创意生成并保持了作者的自主权，同时揭示了对更精细的搜索控制、更紧密的聊天画布整合以及更灵活的视觉编辑的需求。这些见解细化了我们对AI辅助幽默写作的理解，并指导了未来创意写作工具的发展。
英文摘要：
Thematic jokes are central to stand-up comedy, sitcoms, and public speaking, where contexts and punchlines rely on fresh material - news, anecdotes, and cultural references that resonate with the audience. Recent advances in Large Language Models (LLMs) have enabled interactive joke generation through conversational interfaces. Although LLMs enable interactive joke generation, ordinary conversational interfaces seldom give creators enough agency, control, or timely access to such source material for constructing context and punchlines. We designed Jokeasy, a search-enabled prototype system that integrates a dual-role LLM agent acting as both a material scout and a prototype writer to support human-AI collaboration in thematic joke writing. Jokeasy provides a visual canvas in which retrieved web content is organized into editable inspiration blocks and developed through a multistage workflow. A qualitative study with 13 hobbyists and 5 expert participants (including professional comedians and HCI/AI specialists) showed that weaving real-time web material into this structured workflow enriches ideation and preserves author agency, while also revealing needs for finer search control, tighter chat-canvas integration, and more flexible visual editing. These insights refine our understanding of AI-assisted humour writing and guide future creative-writing tools.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
