AutoPR：让您的学术晋升自动化！

摘要

随着同行评审研究数量的激增，学者们日益依赖社交平台进行文献发现，而作者们则投入大量精力推广其工作，以确保可见性和引用率。为简化这一过程并减少对人力的依赖，我们引入了自动推广（AutoPR）这一新任务，旨在将研究论文转化为准确、引人入胜且时效性强的公开内容。为支持严谨评估，我们发布了PRBench，一个多模态基准测试，将512篇同行评审文章与高质量推广帖子相链接，从三个维度评估系统性能：保真度（准确性与语气）、参与度（受众定位与吸引力）以及一致性（时机与渠道优化）。此外，我们提出了PRAgent，一个多代理框架，通过三个阶段自动化AutoPR：多模态准备的内容提取、协作合成以产出精炼内容，以及平台特定适配，优化规范、语气和标签以实现最大覆盖。与直接在PRBench上使用LLM管道相比，PRAgent展现出显著改进，包括总观看时间增长604%，点赞数提升438%，整体参与度至少提高2.9倍。消融研究表明，平台建模与定向推广对这些增益贡献最大。我们的成果将AutoPR定位为一个可处理、可衡量的研究问题，并为可扩展、有影响力的自动化学术交流提供了路线图。

English

As the volume of peer-reviewed research surges, scholars increasingly rely on social platforms for discovery, while authors invest considerable effort in promoting their work to ensure visibility and citations. To streamline this process and reduce the reliance on human effort, we introduce Automatic Promotion (AutoPR), a novel task that transforms research papers into accurate, engaging, and timely public content. To enable rigorous evaluation, we release PRBench, a multimodal benchmark that links 512 peer-reviewed articles to high-quality promotional posts, assessing systems along three axes: Fidelity (accuracy and tone), Engagement (audience targeting and appeal), and Alignment (timing and channel optimization). We also introduce PRAgent, a multi-agent framework that automates AutoPR in three stages: content extraction with multimodal preparation, collaborative synthesis for polished outputs, and platform-specific adaptation to optimize norms, tone, and tagging for maximum reach. When compared to direct LLM pipelines on PRBench, PRAgent demonstrates substantial improvements, including a 604% increase in total watch time, a 438% rise in likes, and at least a 2.9x boost in overall engagement. Ablation studies show that platform modeling and targeted promotion contribute the most to these gains. Our results position AutoPR as a tractable, measurable research problem and provide a roadmap for scalable, impactful automated scholarly communication.

AutoPR：让您的学术晋升自动化！

AutoPR: Let's Automate Your Academic Promotion!

摘要

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