Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach

• URL: http://arxiv.org/abs/2406.06556v1
• Date: Sat, 1 Jun 2024 07:49:31 GMT
• Title: Enhancing Presentation Slide Generation by LLMs with a Multi-Staged End-to-End Approach
• Authors: Sambaran Bandyopadhyay, Himanshu Maheshwari, Anandhavelu Natarajan, Apoorv Saxena,
• Abstract summary: 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. We propose 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.
• Score: 21.8104104944488
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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