SlideBot: A Multi-Agent Framework for Generating Informative, Reliable, Multi-Modal Presentations

TL;DR

SlideBot is a multi-agent framework that leverages LLMs, retrieval, and structured planning to generate reliable, informative, and customizable educational presentation slides, improving accuracy and instructional quality.

Contribution

It introduces a modular, multi-agent system integrating LLMs with retrieval and planning, grounded in instructional design principles, to enhance educational slide generation.

Findings

Improves conceptual accuracy and clarity of slides

Enhances instructional value through expert and student feedback

Streamlines slide creation process in higher education

Abstract

Large Language Models (LLMs) have shown immense potential in education, automating tasks like quiz generation and content summarization. However, generating effective presentation slides introduces unique challenges due to the complexity of multimodal content creation and the need for precise, domain-specific information. Existing LLM-based solutions often fail to produce reliable and informative outputs, limiting their educational value. To address these limitations, we introduce SlideBot - a modular, multi-agent slide generation framework that integrates LLMs with retrieval, structured planning, and code generation. SlideBot is organized around three pillars: informativeness, ensuring deep and contextually grounded content; reliability, achieved by incorporating external sources through retrieval; and practicality, which enables customization and iterative feedback through instructor collaboration. It incorporates evidence-based instructional design principles from Cognitive Load Theory (CLT) and the Cognitive Theory of Multimedia Learning (CTML), using structured planning to manage intrinsic load and consistent visual macros to reduce extraneous load and enhance dual-channel learning. Within the system, specialized agents collaboratively retrieve information, summarize content, generate figures, and format slides using LaTeX, aligning outputs with instructor preferences through interactive refinement. Evaluations from domain experts and students in AI and biomedical education show that SlideBot consistently enhances conceptual accuracy, clarity, and instructional value. These findings demonstrate SlideBot's potential to streamline slide preparation while ensuring accuracy, relevance, and adaptability in higher education.