PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides

Hao Zheng, Xinyan Guan, Hao Kong, Jia Zheng, Weixiang Zhou +5 more
1/7/2025
cs.AIcs.CL

No official code found. Best implementation: icip-cas/PPTAgent (4,769 stars, MIT, last commit 2026-04-28).

Abstract

Automatically generating presentations from documents is a challenging task that requires accommodating content quality, visual appeal, and structural coherence. Existing methods primarily focus on improving and evaluating the content quality in isolation, overlooking visual appeal and structural coherence, which limits their practical applicability. To address these limitations, we propose PPTAgent, which comprehensively improves presentation generation through a two-stage, edit-based approach inspired by human workflows. PPTAgent first analyzes reference presentations to extract slide-level functional types and content schemas, then drafts an outline and iteratively generates editing actions based on selected reference slides to create new slides. To comprehensively evaluate the quality of generated presentations, we further introduce PPTEval, an evaluation framework that assesses presentations across three dimensions: Content, Design, and Coherence. Results demonstrate that PPTAgent significantly outperforms existing automatic presentation generation methods across all three dimensions.

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Code Implementations(1)

icip-cas/PPTAgentCommunity100%
MIT

An Agentic Framework for Reflective PowerPoint Generation

4,769564Shell, PythonJan 4, 20255 months agoMIT
agentagentic-aillmmcpopenclaw+2 more

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Cite this paper

@article{zheng2025pptagent,
  title  = {PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides},
  author = {Hao Zheng and Xinyan Guan and Hao Kong and Jia Zheng and Weixiang Zhou and Hongyu Lin and Yaojie Lu and Ben He and Xianpei Han and Le Sun},
  year   = {2025},
  eprint = {2501.03936},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2501.03936v3}
}

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