Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions

Fuente: arXiv
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Autores principales: Zhou, Kun, He, Jiakai, Yang, Wenmian, Wang, Zhensheng, Zhang, Yiquan, Jia, Weijia
Formato: Preprint
Publicado: 2026
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author Zhou, Kun
He, Jiakai
Yang, Wenmian
Wang, Zhensheng
Zhang, Yiquan
Jia, Weijia
author_facet Zhou, Kun
He, Jiakai
Yang, Wenmian
Wang, Zhensheng
Zhang, Yiquan
Jia, Weijia
contents Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Existing automation methods mostly follow fixed template filling and cannot support dynamic updates for diverse, user-authored slide decks. We therefore define "Dynamic Slide Update via Natural Language Instructions on User-provided Templates" and introduce DynaSlide, a large-scale benchmark with 20,036 real-world instruction-execution triples (source slide, user instruction, target slide) grounded in a shared external database and built from business reporting slides under bring-your-own-template (BYO-template) conditions. To tackle this task, we propose SlideAgent, an agent-based framework that combines multimodal slide parsing, natural language instruction grounding, and tool-augmented reasoning for tables, charts, and textual conclusions. SlideAgent updates content while preserving layout and style, providing a strong reference baseline on DynaSlide. We further design end-to-end and component-level evaluation protocols that reveal key challenges and opportunities for future research. The dataset and code are available at https://github.com/XiaoZhou2024/SlideAgent.
format Preprint
id arxiv_https___arxiv_org_abs_2604_17894
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions
Zhou, Kun
He, Jiakai
Yang, Wenmian
Wang, Zhensheng
Zhang, Yiquan
Jia, Weijia
Computation and Language
Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Existing automation methods mostly follow fixed template filling and cannot support dynamic updates for diverse, user-authored slide decks. We therefore define "Dynamic Slide Update via Natural Language Instructions on User-provided Templates" and introduce DynaSlide, a large-scale benchmark with 20,036 real-world instruction-execution triples (source slide, user instruction, target slide) grounded in a shared external database and built from business reporting slides under bring-your-own-template (BYO-template) conditions. To tackle this task, we propose SlideAgent, an agent-based framework that combines multimodal slide parsing, natural language instruction grounding, and tool-augmented reasoning for tables, charts, and textual conclusions. SlideAgent updates content while preserving layout and style, providing a strong reference baseline on DynaSlide. We further design end-to-end and component-level evaluation protocols that reveal key challenges and opportunities for future research. The dataset and code are available at https://github.com/XiaoZhou2024/SlideAgent.
title Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions
topic Computation and Language
url https://arxiv.org/abs/2604.17894