Hugging Face Trending Papers
Sep 2

SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts

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 Computer Vision
Sep 4

SLIDEFORGE: An LLM Agent for Controllable Editing of Slides as Structured Artifacts

SLIDEFORGE is a new AI agent designed for controllable editing of presentation slides. It constructs a Deck State Graph that links visual decomposition, native PowerPoint object structure, and perceptual organization, enabling theme‑preserving reconstruction through slide‑native operations and rendered‑state verification. The authors also propose an evaluation framework that jointly measures component recovery, preservation, restyling consistency, visual quality, and native editability, and demonstrate that SLIDEFORGE outperforms existing prompting, screenshot‑based, and generic code‑agent baselines.

By Haozhen Zheng, Fulin Wang, Tianhu Xiong, Yingjie Yu, Shengyi Qian, Hanchao Yu, Alex Schwing, Klara Nahrstedt, Mingyuan Wu
arXiv AI
Aug 25

SlideGen: Collaborative Multimodal Agents for Scientific Slide Generation

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