Method illustrations (MIs) play a crucial role in conveying the core ideas of scientific papers, yet their generation remains a labor-intensive process. Here, we take inspiration from human authors' drawing practices and correspondingly propose \textbf{FigAgent}, a novel multi-agent framework for high-quality automatic MI generation. Our FigAgent distills drawing experiences from similar components across MIs and encapsulates them into reusable drawing middlewares that can be orchestrated for MI generation, while evolving these middlewares to adapt to dynamically evolving drawing requirements. Besides, a novel Explore-and-Select drawing strategy is introduced to mimic the human-like trial-and-error manner for gradually constructing MIs with complex structures. Extensive experiments show the efficacy of our method.

翻译：方法插图在传达科学论文核心思想中起着关键作用，然而其生成过程仍是一项劳动密集型任务。在此，我们从人类作者的绘制实践中汲取灵感，相应地提出了**FigAgent**，一种用于高质量自动方法插图生成的新型多智能体框架。我们的FigAgent从跨方法插图的相似组件中提炼绘制经验，并将其封装为可重用的绘制中间件，这些中间件能够被编排用于生成方法插图，同时不断演化这些中间件以适应动态变化的绘制需求。此外，我们引入了一种新颖的“探索-选择”绘制策略，以模拟人类试错式的逐步构建复杂结构方法插图的过程。大量实验证明了我们方法的有效性。