SlideGen is a collaborative vision‑language multi‑agent framework designed to generate scientific presentation slides from research papers. It assigns specialized agents to outline the presentation structure, align figures and tables with key claims, generate speaker notes, and compose editable PPTX slides using a diverse layout library. The system introduces a geometry‑aware density metric to evaluate visual clutter and demonstrates significant improvements in layout balance, content coverage, and text coherence over existing baselines on a 200‑paper benchmark.
By Xin Liang, Zhilin Zhang, Xiang Zhang, Haoran Su, Yiwei Xu, Siqi Sun, Chenyu You
arXiv:2609.00226v1 Announce Type: new
Abstract: Automatic academic paper-to-slide generation is inherently iterative, because creating an effective presentation requires repeated cycles of generation...
By Tarik Can Ozden, Sachidanand VS, Furkan Horoz, Ozgur Kara, Dilek Hakkani-T\"ur, Junho Kim, James Matthew Rehg
arXiv:2606. 19256v1 Announce Type: new Abstract: Automatically generating slide decks from source documents is an important application of large language models (LLMs).
By Haodong Chen, Xuanhe Zhou, Wei Zhou, Xinyue Shao, Yanbing Zhu, Bo Wang, Jiawei Hong, Anya Jia, Fan Wu
arXiv:2601.09487v2 Announce Type: replace
Abstract: The rapid evolution of Large Language Models (LLMs) has fostered diverse paradigms for automated slide generation, ranging from code-driven layouts...
By Yunqiao Yang, Wenbo Li, Houxing Ren, Zimu Lu, Ke Wang, Zhiyuan Huang, Zhuofan Zong, Mingjie Zhan, Hongsheng Li
SLIDEFORGE is an LLM‑driven agent designed for controllable editing of slide decks while preserving layout, style, component structure, and native editability. It constructs a Deck State Graph that links visual decomposition, PowerPoint object structure, and perceptual organization, enabling theme‑preserving reconstruction through slide‑native operations and rendered‑state verification. The authors also propose a comprehensive evaluation framework measuring component recovery, preservation, restyling consistency, visual quality, and native editability, and demonstrate that SLIDEFORGE outperforms direct prompting, screenshot‑based agents, and generic code‑agent baselines.
arXiv:2606. 31154v1 Announce Type: cross Abstract: Creating and editing slides is a rich, multimodal activity that is ubiquitous in professional and educational settings, making it an ideal testbed for real-world computer-use agents.
By Apurva Gandhi, Vishwas Suryanarayanan, Raja Hasnain Anwar, Firoz Shaik, Shubhang Desai, Thong Q. Nguyen, Muhammad Taqi Raza, Vishal Chowdhary, Graham Neubig