Generating presentation slides from a long document with multimodal elements such as text and images is an important task. This is time consuming and needs domain expertise if done manually. Existing approaches for generating a rich presentation from a document are often semi-automatic or only put a flat summary into the slides ignoring the importance of a good narrative. In this paper, we address this research gap by proposing a multi-staged end-to-end model which uses a combination of LLM and VLM. We have experimentally shown that compared to applying LLMs directly with state-of-the-art prompting, our proposed multi-staged solution is better in terms of automated metrics and human evaluation.
@article{arxiv.2406.06556,
title = {Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach},
author = {Sambaran Bandyopadhyay and Himanshu Maheshwari and Anandhavelu Natarajan and Apoorv Saxena},
journal= {arXiv preprint arXiv:2406.06556},
year = {2024}
}