用智能提示推荐系统帮用户突破写作瓶颈，激发创意表达。
PromptHelper: A Prompt Recommender System for Encouraging Creativity in AI Chatbot Interactions
- 基于上下文推荐多样化的后续提问建议，支持探索性交互
- 实验证明可提升用户感知的探索性和表达力，不增加认知负担
- 适合需要创意启发的写作者或教育场景使用
提示工程是与AI系统交互的核心，但许多用户难以探索不同方向、清晰表达创意意图，或理解提示变化如何影响模型输出。我们提出提示推荐系统（PRS）作为一种交互方式，支持探索，提供上下文相关的后续提示建议。本文展示PromptHelper——一个集成于AI聊天机器人的PRS原型，在用户完成真实写作任务时，提供语义多样的提示建议。我们在一项2×2全被试内实验中评估了PromptHelper（N=32），涵盖创意和学术写作任务。结果表明，PromptHelper显著提升了用户的感知探索度与表达力，且未增加认知负荷。定性分析显示，提示推荐帮助用户拓展新方向，缓解“下一步该问什么”的不确定性，并更准确地表达意图。我们讨论了此类设计对保留用户自主权的同时促进探索性交互的意义，并开源相关资源以支持提示推荐研究。
原文摘要 · Abstract (English)
Prompting is central to interaction with AI systems, yet many users struggle to explore alternative directions, articulate creative intent, or understand how variations in prompts shape model outputs. We introduce prompt recommender systems (PRS) as an interaction approach that supports exploration, suggesting contextually relevant follow-up prompts. We present PromptHelper, a PRS prototype integrated into an AI chatbot that surfaces semantically diverse prompt suggestions while users work on real writing tasks. We evaluate PromptHelper in a 2x2 fully within-subjects study (N=32) across creative and academic writing tasks. Results show that PromptHelper significantly increases users' perceived exploration and expressiveness without increasing cognitive workload. Qualitative findings illustrate how prompt recommendations help users branch into new directions, overcome uncertainty about what to ask next, and better articulate their intent. We discuss implications for designing AI interfaces that scaffold exploratory interaction while preserving user agency, and release open-source resources to support research on prompt recommendation.
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