OmniPresent: Generating Coherent Presentation Suites from Scientific Papers

2026-07-01

AI Summary

This work addresses the challenge of automatically transforming static scientific papers into dynamic presentation formats—such as posters, slides, and videos—while preserving semantic consistency across modalities. We formalize this as the Unified Presentation Suite Generation task and propose a centralized content planning framework grounded in renderable HTML. To ensure coherence among multimodal outputs, we introduce a self-correcting verification-and-repair loop. Our contributions include OmniPreBench, a large-scale dataset; a vision-language model–based evaluation protocol; and a method for aligning multimodal content. Experimental results demonstrate that our approach significantly outperforms strong baselines in both factual accuracy and visual appeal, enabling the automatic generation of high-quality, semantically consistent scientific communication materials.

Abstract

Transforming static research papers into dynamic media such as posters, slides, and videos is essential for effective dissemination but remains a labor-intensive challenge. Existing automated approaches often treat these formats in isolation and consequently fail to maintain semantic consistency across the entire presentation suite. We address this fragmentation by formalizing the task of unified presentation suite generation and proposing $\textbf{OmniPresent}$ to orchestrate the creation of coherent deliverables. Our framework adopts a renderable HTML representation to enable centralized content planning and a self-correcting verify-and-repair loop that actively resolves conflicts across modalities. We further facilitate scalable research in this domain by releasing $\textbf{OmniPreBench}$, a comprehensive dataset comprising over one thousand papers with paired artifacts, and establishing a rigorous VLM-based evaluation protocol. Empirical results confirm that our method generates high-quality and faithful presentation suites that significantly surpass strong baselines in both accuracy and visual appeal.

Problem

• presentation suite generation
• scientific paper
• semantic consistency
• multimodal content
• automated dissemination

Innovation

• unified presentation suite generation
• renderable HTML representation
• verify-and-repair loop
• OmniPreBench dataset
• VLM-based evaluation