SlideGen：用于科学幻灯片生成的协作多模态智能体
SlideGen: Collaborative Multimodal Agents for Scientific Slide Generation
AI总结：
SlideGen通过协作多模态智能体实现科学论文到高质量幻灯片的生成，提升视觉质量和内容忠实度。
摘要：
从科学论文生成学术幻灯片是一项具有挑战性的多模态推理任务，需要长上下文理解和有意识的视觉规划。现有方法大多将其简化为纯文本摘要，忽略了幻灯片创建的视觉成分和设计密集特性。在本文中，我们介绍了SlideGen，一种代理、模块化且具有视觉闭环的框架，用于科学论文到幻灯片的生成。SlideGen协调一组视觉语言代理，通过文档结构和语义进行协作推理，生成具有逻辑流程和吸引人的视觉呈现的可编辑PPTX幻灯片。通过整合协调的概述、映射、安排、笔记综合和迭代细化，我们的系统始终能够交付专家级别的幻灯片质量。在多样化的基准测试和强大的基线方法上，SlideGen在视觉质量、内容忠实度和可读性方面均优于现有方法，使其成为自动化幻灯片生成的新状态-of-the-art。我们的工作为设计感知的多模态幻灯片生成奠定了基础，展示了如何通过代理协作在复杂的多模态推理任务中弥合理解和呈现之间的差距。
英文摘要：
Creating presentation slides from scientific papers is not simply a matter of summarizing paragraphs. A presenter is required to decide what story to tell, which figures and equations to highlight, and how to arrange them into pages that are visually clear rather than crowded or repetitive. The need to jointly reason over long contexts and layout-sensitive design makes paper-to-slide generation a uniquely challenging multimodal task. Most existing approaches, however, focus mainly on textual content selection, producing slides that often lack visual balance, narrative flow, or coherent integration of multimodal evidence. In this work, we introduce SlideGen, a collaborative vision-language multi-agent framework that coordinates narrative planning, multimodal grounding, and layout composition. SlideGen assigns specialized agents to outline the presentation structure, align supporting figures and tables with key claims, generate speaker notes, and compose editable PPTX slides through a diverse layout library. By refining layouts at the deck level, the system produces slide decks that are both faithful to the source paper and effective as presentations. To evaluate slide generation beyond text fidelity, we propose geometry-aware density (GAD), a metric that captures visual clutter, sparsity, and fragmentation, and shows strong agreement with human judgments. Evaluated across four complementary dimensions on our 200-paper benchmark, SlideGen consistently and significantly improves layout balance, content coverage, and text coherence, outperforming competitive baselines in paper-to-slide generation. Our findings suggest that effective slide generation requires multimodal design reasoning, and that agent collaboration offers a principled bridge between document understanding and scientific communication.
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。
