DeepPresenter：基于环境锚定的智能演讲生成反思框架

摘要

演示文稿生成需要深入的内容研究、连贯的视觉设计以及基于观察的迭代优化。然而现有的演示文稿生成工具往往依赖预定义流程和固定模板。为此，我们提出DeepPresenter——一种能适应用户多样化意图、支持有效反馈驱动优化、并突破脚本化流程限制的智能框架。该框架通过自主规划、渲染和修订中间幻灯片成果物，实现对环境观察的长周期优化。与依赖内部信号（如推理轨迹）的自我反思不同，我们的环境锚定反思机制将生成过程建立在可感知的成果物状态（如已渲染幻灯片）之上，使系统能在执行过程中识别并修正演示文稿特有的问题。在涵盖多样化演示场景的评估集上，DeepPresenter实现了最先进的性能，且微调后的90亿参数模型在成本显著降低的同时仍保持强大竞争力。项目地址：https://github.com/icip-cas/PPTAgent

English

Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing presentation agents often rely on predefined workflows and fixed templates. To address this, we present DeepPresenter, an agentic framework that adapts to diverse user intents, enables effective feedback-driven refinement, and generalizes beyond a scripted pipeline. Specifically, DeepPresenter autonomously plans, renders, and revises intermediate slide artifacts to support long-horizon refinement with environmental observations. Furthermore, rather than relying on self-reflection over internal signals (e.g., reasoning traces), our environment-grounded reflection conditions the generation process on perceptual artifact states (e.g., rendered slides), enabling the system to identify and correct presentation-specific issues during execution. Results on the evaluation set covering diverse presentation-generation scenarios show that DeepPresenter achieves state-of-the-art performance, and the fine-tuned 9B model remains highly competitive at substantially lower cost. Our project is available at: https://github.com/icip-cas/PPTAgent

DeepPresenter：基于环境锚定的智能演讲生成反思框架

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

摘要

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