DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation
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
69aea6af9893f58272f742c2
Hao Zheng
claimed_verified
2026-03-09T11:05:59.145Z
64380d17819f3ab20d17595b
https://cdn-avatars.huggingface.co/v1/production/uploads/64380d17819f3ab20d17595b/LW_JVO54BCoYnKYZ-868o.png
Zheng Hao
Forceless
user
Forceless
69aea6af9893f58272f742c3
Guozhao Mo
69aea6af9893f58272f742c4
Xinru Yan
69aea6af9893f58272f742c5
Qianhao Yuan
69aea6af9893f58272f742c6
Wenkai Zhang
69aea6af9893f58272f742c7
Xuanang Chen
69aea6af9893f58272f742c8
Yaojie Lu
69aea6af9893f58272f742c9
Hongyu Lin
69aea6af9893f58272f742ca
Xianpei Han
69aea6af9893f58272f742cb
Le Sun
DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation
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 is an agentic framework for presentation generation that adaptively plans and refines slide artifacts through environment-grounded reflection, achieving state-of-the-art performance with reduced computational costs.
agentic framework presentation generation environment-grounded reflection slide artifacts iterative refinement long-horizon refinement